Category Archives: Knowledge

SUSTAINABLE APPLIED EMPIRICAL THEORIES [SAET]. Basics

eJournal: uffmm.org
ISSN 2567-6458, 14.April 2022 – 14.April 2022
Email: info@uffmm.org
Author Writing: Gerd Doeben-Henisch
Authors in Discourse: Gerd Doeben-Henisch & Philipp Westermeier
Email: gerd@doeben-henisch.de

— not yet finished !! —

BLOG-CONTEXT

This post is part of the Philosophy of Science theme which is part of the uffmm blog.

PREFACE

In preceding papers about the concept of an Empirical Theory [ET], especially in the context of Karl Popper (e.g.Popper and Empirical Theory. A conceptual Experiment ) it has been investigated whether and how these concepts can be merged with the idea of a development process (e.g. An Empirical Theory as a Development Process ). Another aspect is the idea of ‘sustainable development’ as it has been characterized by the so-called Brundtland report [1] in 1987, which laid the ground for the United Nations Rio conference ‘Earth Summit’ in 1992 [2] which ended after several more UN conferences up in 2015 with the ‘Agenda 2030’ propagating 17 ‘Sustainable Development Goals’ (SDGs). [3]

‘Sustainability’ depends on the ability to make ‘qualified estimates about possible future states’. This again presupposes qualified knowledge about the ‘past’ and the ‘present’. Especially should this knowledge contain those kinds of ‘elaborated changes’ in the sequence of events which can be interpreted and used as ‘patterns of possible changes’ leading from one observed situation to another observable situation. Starting from here the following text communicates some more ideas.

SAET BASICS

This figure shows three different layers in the construction of an applied empirical theory: (i) On a ‘meta level’ some natural experts are communicating, are observing some parts the empirical environment, and try to describe these ideas with some symbolic expressions of a shared natural language. (ii) The content of these meta-level activities produces three kinds of texts as an ‘object level’: (a) One text describes the observed given situation with interesting properties; (b) another text describes the requirements for some wanted situation in a future state; (c) another text describes a collection of ‘change rules’ of possible actions which are assumed to be able a given situation to a new situation. (iii) On a third level called ‘philosophical level’ one can raise questions to the ‘conditions’ of all the elements used on the meta level.

SAET DYNAMIC SPACES

This figure is ‘zooming into’ a process described by an object level of a SAET. The ‘given state’ of a concrete SAET describes some part of the empirical environment which as such has some ‘dynamics’, but one can additionally describe individual actors as parts of the environment. Every actor has its own dynamics and viewed in isolation he is able to produces a set of states by its actions. ‘Potentially’ nearly non-countable many possible continuations are possible. Thus every actor is associated with a ‘space of possible continuations’ called ‘potential individual realization space’ [PIRS]. In reality every actor must all the time ‘decide’ which concrete continuation shall be selected from many possible continuations. Thus the large space will be transformed into a single process representing only one path in the PIRS. If one is asking what are the ‘factors’ influencing the selection process one can detect many kinds of factors. Besides the internal factors there is the ‘environment as such’: No water to drink; no food to eat; deadly criminals around you … this will hinder every child to select those options which would be helpful. The in the realm of the ‘internal states’ there is a certain amount of ‘experience’ enabling certain kinds of ‘knowledge’ which is the point of reference for possible decisions. If this experience is too small, if the knowledge is wrong, there exists no chance to produce good selections. And much more…

SAET MULTIPLE THEORIES

This figure is again looking from the meta level. Usually there is more than one theory written down. Mostly these theories are dealing with different aspects of the empirical reality. Because the reality as such is ‘one’ it would be helpful to ‘unify all different special views’. In a SEAT like theory as described here this is quite simple: one has only to unify each kind of text as the ‘given situation’, the ‘wanted situation’ as well as the ‘change rules’ to get a new ‘unified’ theory.

COMMENTS

[1] Report of the World Commission on Environment and Development, https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf, accessed: 10/04/2022

[2] Report of the United Nations Conference on Environment and Development, https://documents-dds-ny.un.org/doc/UNDOC/GEN/N92/836/55/PDF/N9283655.pdf, accessed: 10/04/2022

[3] United Nations, https://sdgs.un.org/goals, accessed 10/04/2022

EMPIRICAL THEORY – (COLLECTIVE) INTELLIGENCE – INTELLIGENT MACHINES. An Introduction

eJournal: uffmm.org
ISSN 2567-6458, 9.April 2022 – 9.April 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

— not yet finished !! —

BLOG-CONTEXT

This post is part of the Philosophy of Science theme which is part of the uffmm blog.

PREFACE

In an elderly post from 2017 I have developed the concept of ‘Intelligent Machines’ by using the paradigm of ‘Distributed Actor Actor Interactions‘ which includes the concept of an ‘Actor Story’. Meanwhile the DAAI paradigm has been ’embedded’ in the more general concept of an ‘Applied Empirical Theory’ [1], which can immediately being used as a ‘simulation’. The ‘content’ is the same, only the ‘format’ is different. But to use the concept of an ‘applied empirical theory’ in this dynamic way directly as a simulation needs a ‘tool’ which is a piece of software called ‘oksimo (reloaded)’ [2] which is located on a server (see: oksimo.com) which can be used via an interactive web-page.[3]

This new format of an applied empirical theory [AET] is producing during simulation a process which can be understood as an inference chain. Doing all possible inference chains this produces a graph of processes, whose nodes are situations. This corresponds directly to the ‘actor story’ [AS] as a central part of the DAAI paradigm.

Knowing this it makes some sense to re-think the concept of ‘intelligent machine’ [IM] within the concept of an applied empirical theory, especially in the format of a dynamic simulation.

Until now the language games of ‘intelligence’ or ‘intelligent algorithms’ or something like this are not yet an established part of the classical theory concepts.

EMPIRICAL THEORY – (COLLECTIVE) INTELLIGENCE – INTELLIGENT MACHINE. Introduction

… to be done …

COMMENTS

[1] See as a first description HERE.

[2] The name ‘oksimo’ is ‘reloaded’ from an earlier project of the author around 2009 which is described in the German wikipedia under ‘oksimo‘. ‘oksimo’ was an acronym for ‘Open Knowledge Simulation MOdeling’. The ‘new oksimo’ or ‘oksimo reloaded’ repeats this vision mostly but is rather more extended and implemented in a completely different way.

[3] At the time of this writing the software is still only open for those who are participating in the testing phase. We are working with level 2 of the software (normal language extended with math) while we are already preparing level 3 (a more comfortable GUI to edit ‘complete empirical theories’).

Pierre Lévy : Collective Intelligence – Chapter 8 –Anthropological Space

eJournal: uffmm.org, ISSN 2567-6458,
6.April 2022 – 15.May 2022, 09:30h
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

SCOPE

In the uffmm review section the different papers and books are discussed from the point of view of the oksimo paradigm. [1] In the following text the author discusses chapter 8 of the book “Collective Intelligence. mankind’s emerging world in cyberspace” by Pierre Lévy (translated by Robert Bonono),1997 (French: 1994)[2]

CONTEXT

In a proceeding post the chapter 7 of Lévy’s book has been discussed. Here follows chapter 8.

Chapter 8: Anthropological Space

POSITION LÉVY

In this chapter Lévy characterizes the ‘Anthropological Space’ following some heading ideas like ‘Signification’, ‘Structuring effects’, followed by ‘Planes’ and ‘Velocities’.

The Multiple Spaces of Signification

Lévy starts his considerations with the statement, that “A simple conversation could be seen as the shared construction of a virtual space of signification, which each speaker attempts to shape according to his mood and intentions.” (p.143) And in another step he is looking from the outside of messages onto the messages as objects being part of a complex situation where messages are examples of interactions between individual speakers/ hearers, which are part of an overall situation, and where the messages are “evoking representations” in the individuals. The situation is not an ‘untouched something’ but the individuals are part of it, reacting to the situation by actions and thereby they are changing the situation. Thus, Lévy can state “Our interactions produce, transform, and continuously develop heterogeneous and interlinked spaces.” (p.143)

The general schema seems therefore to be ‘interactions produce spaces’ in a somehow general meaning, and ‘messages’ are a special kind of ‘interactions’ and these special interactions as messages produce special spaces characterized as ‘spaces of signification’.

The general concept of ‘(anthropological) space’ assumes that these spaces are “living” and “relativistic” with regard to the “objects” they contain and which “organize them”. (cf.143)

Another aspect is the occurrence in time: Lévy distinguishes spaces which are more “evanescent” compared to others, which are more “durable”. (cf. p.143f)

“Being larger” is also an aspect of an anthropological space. This kind of ‘largeness’ depends an the number of participating interacting individuals and objects, tools and other artifacts.(cf. p.144)

“The importance” of an “event” in its “sphere” can be “recognized” by its ability to “reorganize the proximities and distances in a given space”, and to create “new space time(s)”…” (cf. p.144)

Different kinds of spaces are mentioned as “physical”, “geometric”, “emotional, aesthetic, social and historical”, spaces of “signification in general”. (cf. p.144) This view summarizes this in the statement “we live in thousands of different spaces, each with its own system of proximity (temporal, emotional, linguistic, etc.) such that a given entity can be near us in one space, yet quite distant in another. Each space has its own axiology, its own system of values or measurements.”(p.144)

A good part of our “cognitive activity” and of “time” is used to navigate through these spaces, to operate on these in different ways. (cf. p.145)

Structuring, Living, Autonomous, Irreversible
In the age of an increasing digitization of everything the basic reading of a normal text with the associated processing of interpretation seems to ‘fade out’ slowly and in silence. But — as Lévy circumscribes in a wonderful way — all ‘outer effects’ of humankind are rooted in the inner dynamics of individual people enabling a collective intelligence, a collective understanding, by using symbolic expressions as the main signals between different brains. ‘As such’ these signals have ‘no meaning’, but interwoven with all the other experiences they can become ‘loaded with meaning’ which can be encoded and decoded by these symbolic expressions and thereby can become a ‘trigger’ for other brains to organize some ‘triggered meaning’ as a mean for understanding. But this ‘encoding and decoding’ is not an isolated process but as such already interwoven in a network of interactions called ‘learning process’; it is culturally embedded. What you can see in the figure above are additional marks in the text produced by the reader of this text to underline those parts of the expressions which appear for the reader as strongly related to his understanding of the text and thereby pointing to ‘building blocks’ of the rising understanding inside of the reader what he presupposes to be the ‘intention’ of the writer of this text. As everybody can control in the light of the own interpretation experience such a ‘re-construction’ is always in danger to reconstruct something which is not the intention of the author. Without further clues the interpreting reader is ‘lost in an approaching understanding’.

In this section Lévy brings forward the question, what the “specific characteristics” of the four anthropological spaces are, which he had described so far.(p.145) And in front of a puzzle of disturbing aspects he points to the heart of everything: all these aspects “are engendered by the practical and imaginative activity of millions of beings, by anthropological machines that work within the recesses of their subjects …”.(p.145)

Although these distinguished four anthropological spaces are in a certain sense “structuring” by their objective and interactive materiality, they should not be misunderstood as purely “abstract” properties within some understanding. In the contrary, they are “living worlds continuously engendered by the processes and interactions that unfold within them.”(p.146) And this grounding insight in the nature of the anthropological spaces is reverberating in every of these spaces.

Thus, “the knowledge space” isn’t simply “the subject of cognitive science”. It isn’t some kind of an “abstract container for all possible knowledge”. (cf. p.146) It is an “ongoing anthropological creation, it is a living plane, qualitatively differentiated by … the collective intellects that pass through it.”(cf. p.146)

Similarly, the commodity space is not “the subject of a specific social science”, but it is “a world that has grown and developed autonomously , … self-organized, creative, destructive.” (cf. p.146)

Despite is manifest character it is not “unthinkable” that these different spaces would again disappear in the future. When this would happen then this would be a “terrifying catastrophe, a deadly chaos”. The close connection between earth and humanity point to a kind of “irreversibility” which motivates the qualification of these spaces as “anthropological spaces”. (cf. p.147)

Planes of Existence, Contingent and Eternal Velocities

As an introductory phrase one could here perhaps select the following: “Anthropological spaces in themselves are neither infrastructures nor superstructures but planes of existence, frequencies, velocities, determined within the social spectrum.”(p.147) And fundamentally “the appearance of anthropological spaces is in no way governed by necessity.”(p.148) This motivates the statement, that anthropological spaces are ‘contingent’.(cf. p.148) Otherwise, this statement contrasts in some sense with the statement, that anthropological spaces, “once they have shaped … they become timeless, as if they had always already have been there.”(p.148) And Lévy infers from this ‘irreversibility of anthropological spaces’ that “these effect the past as well.”(cf. p.148) A hint for this flexibility, for this astonishing dynamics of anthropological spaces is given in the statement, that anthropological spaces “are worlds of signification and not rarefied categories sharing physical objects…” (p.149) An anthropological cartography using categories which “serves only to separate, classify, or isolate, we should abandon it at once.”(p.150) The main challenge is “to clear the way … which traces the lines to the future.”(p.149)

Somehow hidden, as an accompanying framework, within which the anthropological spaces are emerging, Lévy uses continuously the concepts of ‘earth’, ‘territory’, ‘capital’, and ‘virtual space of knowledge’ (cf. p.150) like a ‘coordinate space’, which outlines an undefined space-like something.

COMMENTS ON LÉVY

Here some comments on the position of Lévy.

The Multiple Spaces of Signification

This chapter is a bit challenging on account of the different usages of the term ‘space’. In one sense ‘space’ is associated with ‘interaction in general’ where the production of ‘messages’ (mediated by statements/ utterances) is only one special kind of interaction.

A space in general is characterized by its ‘ingredients’ realized by individual actors, used objects, artifacts, kinds of interactions, usage in time (evanescent or more durable), etc.

A ‘message-born space’ is not a ‘real space’ like those interaction-based spaces with real objects, real effects, but a purely ‘cognitive space of meanings’ associated with the used language expressions and the associated ‘meaning function’ rooted in the ‘individual speaker’ which is ‘member’ of a cultural space with specific meanings induced by social learning.

Because all ‘real spaces’ have automatically a cognitive counterpart in the acting individual which to some extend is encoded as meaning of the used language, there exists a subtle relationship between ‘spaces in general’ and ‘spaces of meaning (significance)’: both spaces are — by meaning — close together, but they are — nevertheless — different! Spaces of meaning can ‘reflect’ the ‘dynamics of real spaces’ ‘sufficiently well’, and if this is the case then they are ‘helpful’ and can be classified as being ’empirically sound’ (true); if the ‘dynamics of real spaces’ is ‘not sufficiently well’ reflected, then they are ‘less helpful’ and can be classified as being ‘not empirically sound’ (false).

For the survival of biological populations on the planet earth it seems to be of vital importance that the ’empirical soundness’ of the space of meaning’ is ‘good enough’.

Things would be too simple if the criterion of ’empirical soundness’ would be sufficient. As one can learn from the ‘evolution of life’ the available ‘knowledge’ of the empirical environment at a certain point of time is only of limited help, as long as the upcoming ‘future’ is widely ‘unknown’. This ‘unknown character’ of the future results from the real dynamics and complexity of the overall process of empirical reality, which principally can not be predicted. Therefore that part of knowledge which influences the real behavior must contain a ‘minimum of unclassified knowledge’ which — at least in the past of life on this planet — was the reason, why life survived.

Comments on Structuring, Living, Autonomous, Irreversible

The text of Lévy continuous to be very dense, compact, partially nearly poetic, but nevertheless the text is revealing a strong analytic power keeping the ‘balls in the air’ and thereby ‘keeping all tensions alive’.

For me as a reader with a special background most amazing is his handling of the relationship between the richness of the ‘outer appearance’ of humankind in many dimensions (earth, territory, commodity, knowledge) and the grounding of all these in the inner dynamics of the acting individuals, not as isolated entities, but interwoven by interactions, which not only have their objective impact in the outer world of bodies, but simultaneously also in the inner world of subjectivity with a very special internal dynamic structure.

Neither the ‘inner dynamics as such’ nor the ‘outer effects as such’ taken apart can tell the story about humankind. The main ‘secret’ is given in this special way how the ‘outer world’ and the ‘inner world’ continuously, permanently, always are ‘vibrating together’: the outer world is brought to the inner world through a mediating body which ‘feeds’ a part of the body called ‘brain’, and the brain again ‘transforms’ these modified outer world events in new structures of a radical different reality, the ‘inner reality’, a ‘virtual reality’ compared to the ‘outer reality’ which is not known ‘as such’, but only known in the mode of ‘already transformed signals’ which are ‘further processed by the inner dynamics’ of the brain.

Humankind, a collection of interacting individual brains, appears in this view as a special environment with special laws ruling this environment, in which the outer world is ‘received’ as something ‘different’, but given as ‘clouds of single signals’ which are ‘caught’ by ‘filtering’ these clouds as ‘sequences of events’ partitioned by many different ‘patterns’ indicating ‘possible structures’ for further ‘processing’. And while this is happening all the time the outer world is a ‘hybrid’ world consisting of non-human parts and humankind together where this hybrid ‘outer-inner-being’ is continuously modified by the human as well as outer activities. Thus, human actors perceiving the outer world do not perceive the outer world ‘independent of humans’, but always ‘entangled with humans’, with ‘humankind’. This entanglement is not really new because since the rising of life on this planet earth we can observe this entanglement of life-free earth and life as the new live-earth where the earth is ‘cocooned with the biosphere’ which from the early beginnings started to modify the earth. But somehow new is this special ability of humankind — thereby surpassing all the other life forms — to ‘cognitively see itself as part of the outer world’ and ‘understand itself as a really moving something’ which can and does ‘change the earth-life being’. There is less and less no more only one ‘earth’ and only some biological ‘life’, no, there is since the advent of humankind now only an ‘earth-life being’ (ELB) which is ‘irreversible’ and whose ‘fate’ is somewhere in a future state of a ‘knowing earth-life being’ which ‘knows about itself’, which is an ’emotional something’ of new dimensions.

The today widespread vision of ‘intelligent machines’ will be remembered as the dream of ‘children’ which didn’t yet understand that not the machine in front of them (built by them) is the real wonder, but they as the ‘children’ are the original wonder, which can built such machines and which can built much more, an ‘earth-life being’ of nearly infinite order.

In the light of these ideas the manner of speaking of ‘anthropological spaces’ appears slowly ‘questionable’. A human being as the ‘prototype’ of an ‘outer-inner transformer’ is never something ‘completely different’ to the outer body world, and the body world is never isolated from the ‘inner world’ of bodies. And the synergies between outer-inner-transformers resulting in a new kind of ‘collective intelligence’ is again not separated from the outer body world, but manifests a new morphological earth-life-being where the so-called ‘anthropological spaces’ are only different manifestations of this unique earth-life-being. The idea of ‘human kind’ as something special is only important for a ‘taxonomy’ between the different species of biological manifestations, but the biosphere as a whole is finally not a ‘foreign something’ to the earth, not to the solar system, not to the milky way galaxy [3], even not to the whole universe. The biosphere is an ‘outcome’ of the earth system because the so-called ‘material world’ is — as we can know today — not something ‘dead substance’ but the most dynamic something we can know. And biological life as we know it is nothing else than one of the outcomes of the radical ‘freedom’ rooted in these maximal dynamics of the ‘matter-energy something’ partially revealed by quantum mechanics, partially by evolutionary biology.

The primary root of the ‘irreversibility’ of the earth-life-being has then to be located in the primary nature of the earth-life-being itself: the matter-energy-something (MES) contains all these different transformations as its ‘inner potentials’ within its dynamics. Therefore the ’emergence’ of biological systems is an ‘outcome’ of these primary structures and as ‘outcome’ it sheds some light back on the ‘matter-energy-something’. In the beginning of the appearance of the matter-energy-something there was not too much to observe from the outside, but during the existence in time the matter-energy-something produced more and more complex structures which showed up as complete systems of self-reproduction, of self-knowing, of self-knowing even as populations. The self-knowing of the earth, the solar system … will be next. There is no natural ‘boarder’ to stop this … only the system itself can destroy itself. There is no need for destruction, but a real possibility rooted in the fundamental freedom of everything.

Planes of Existence, Contingent and Eternal Velocities

Thus, we have two meta-frames: (i) as common ground Lévy assumes a 4-dimensional coordinate system grounded in what he calls ‘earth’, ‘territory’, ‘capital’, and ‘virtual space of knowledge’, and (ii) then the individual human with his body and knowledge space which is embedded in a stream of infinite interactions between some environment (earth, territory, capital, knowledge space of others) and his own knowledge space. Thus, whatever is ‘real’, it is ‘mediated’ by his knowledge space which can have nearly infinite many ‘sub-spaces’. The ‘same real thing’ can appear in different knowledge spaces as a ‘differently known thing’. Between the knowledge spaces of different humans interactions (partially by symbolic communication) are occurring which can can shape the individual knowledge space with all its sub-spaces. In some sense one can interpret a knowledge sub-space as a ‘plane of events’ representing the ‘plane of existence’, which is basically ‘contingent’ because the knowledge space as such is ‘contingent’. Driven by a dynamic environment as well as by a dynamic knowledge space a dimension of ‘time’ is framing all events, inducing implicitly some order, is making things ‘slow’ or ‘fast’.

One can ask whether his assumed 4-dimensional coordinate system grounded in what he calls ‘earth’, ‘territory’, ‘capital’, and ‘virtual space of knowledge’ is indeed as ‘hard’ as he presupposes?

Thus, ‘territory’ is not a real given object but a ‘minded object’ which can be or not. ‘Capital’ is also a creation of some knowledge-space which is a ‘symbolic instrument’ associated with something different; it has no life on its own. In radical thinking there seem to exist only two dimension: (i) the ‘real world outside’ of the human mind (with the body as part of the real world) and (ii) the human mind (knowledge space) somewhere ‘inside’ the real world. In one sense the ‘real world’ is the primary source for everything, in another sense is the knowledge space the only ‘real space’ embracing everything else as ‘secondary’. From an ‘abstract outside’, from the perspective of some abstract ‘meta space’ is the ‘reality of the knowledge space’ a ‘virtual world’ reconstructing the real world as a virtual structure, which is used by the human body as a ‘guide’ in the real world of bodies.

Re-building the real world inside a virtual world and using the virtual models as guides for a behavior in the real world of bodies this enables the energy-matter of the universe to ‘recognize itself’ in the format of an ‘universal self-consciousness’. As long as the individual virtual knowledge space are more ‘separated’ than ‘unified’ the universal self-consciousness is very ‘dim’, very ‘weak’. To that extend that the individual knowledge spaces are becoming unified the universal self-consciousness can grow. But, this unification can only work in the ‘right way’ if the individual knowledge spaces are ‘as true as possible’ and are ‘communicating as free as possible’. The human history shows numeral examples of ‘crashes’ by ‘imperfectly unified knowledge spaces’.

OTHER COMMENTS

[1] Gerd Doeben-Henisch,The general idea of the oksimo paradigm: https://www.uffmm.org/2022/01/24/newsletter/, January 2022

[2] Pierre Lévy in wkp-en: https://en.wikipedia.org/wiki/Pierre_L%C3%A9vy

[3] Milky Way galaxy in wkp-en: https://en.wikipedia.org/wiki/Milky_Way

AN EMPIRICAL THEORY AS A DEVELOPMENT PROCESS

eJournal: uffmm.org
ISSN 2567-6458, 2.April 22 – 3.April 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

BLOG-CONTEXT

This post is part of the Philosophy of Science theme which is part of the uffmm blog.

PREFACE

In a preceding post I have illustrated how one can apply the concept of an empirical theory — highly inspired by Karl Popper — to an everyday problem given as a county and its demographic problem(s). In this post I like to develop this idea a little more.

AN EMPIRICAL THEORY AS A DEVELOPMENT PROCESS

The figure shows a simplified outline of the idea of an empirical theory being realized during a development process based on the interactions and the communication of citizens as ‘natural experts’.

CITIZENs – natural experts

As starting point we assume citizens understood as our ‘natural experts’ being members of a democratic society with political parties, an freely elected parliament, which can create some helpful laws for the societal life and some authorities serving the need of the citizens.

SYMBOLIC DESCRIPTIONS

To coordinate their actions by a sufficient communication the citizens produce symbolic descriptions to make public how they see the ‘given situation’, which kinds of ‘future states’ (‘goals’) they want to achieve, and a list of ‘actions’ which can ‘change/ transform’ the given situation step wise into the envisioned future state.

LEVELS OF ABSTRACTIONS

Using an everyday language — possibly enriched with some math expressions – one can talk about our world of experience on different levels of abstraction. To get a rather wide scope one starts with most abstract concepts, and then one can break down these abstract concepts more and more with concrete properties/ features until these concrete expressions are ‘touching the real experience’. It can be helpful — in most cases — not to describe everything in one description but one does a partition of ‘the whole’ into several more concrete descriptions to get the main points. Afterwards it should be possible to ‘unify’ these more concrete descriptions into one large picture showing how all these concrete descriptions ‘work together’.

LOGICAL INFERENCE BY SIMULATION

A very useful property of empirical theories is the possibility to derive from given assumptions and assumed rules of inference possible consequences which are ‘true’ if the assumptions an the rules of inference are ‘true’.

The above outlined descriptions are seen in this post as texts which satisfy the requirements of an empirical theory such that the ‘simulator’ is able to derive from these assumptions all possible ‘true’ consequences if these assumptions are assumed to be ‘true’. Especially will the simulator deliver not only one single consequence only but a whole ‘sequence of consequences’ following each other in time.

PURE WWW KNOWLEDGE SPACE

This simple outline describes the application format of the oksimo software which is understood here as a kind of a ‘theory machine’ for everybody.

It is assumed that a symbolic description is given as a pure text file or as a given HTML page somewhere in the world wide web [WWW].

The simulator realized as an oksimo program can load such a file and can run a simulation. The output will be send back as an HTML page.

No special special data base is needed inside of the oksimo application. All oksimo related HTML pages located by a citizen somewhere in the WWW are constituting a ‘global public knowledge space’ accessible by everybody.

DISTRIBUTED OKSIMO INSTANCES

An oksimo server positioned behind the oksimo address ‘oksimo.com’ can produce for a simulation demand a ‘simulator instance’ running one simulation. There can be many simulations running in parallel. A simulation can also be connected in real time to Internet-of-Things [IoT] instances to receive empirical data being used in the simulation. In ‘interactive mode’ an oksimo simulation does furthermore allow the participation of ‘actors’ which function as a ‘dynamic rule instance’: they receive input from the simulated given situation and can respond ‘on their own’. This turns a simulation into an ‘open process’ like we do encounter during ‘everyday real processes’. An ‘actor’ must not necessarily be a ‘human’ actor; it can also be a ‘non-human’ actor. Furthermore it is possible to establish a ‘simulation-meta-level’: because a simulation as a whole represents a ‘full theory’ on can feed this whole theory to an ‘artificial intelligence algorithm’ which dos not run only one simulation but checks the space of ‘all possible simulations’ and thereby identifies those sub-spaces which are — according to the defined goals — ‘zones of special interest’.

THE OKSIMO WORKFLOW for a Global Open Knowledge Space

eJournal: uffmm.org
ISSN 2567-6458, 1.April 2022 – 6.April 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This post is part of the theme called ‘Oksimo Software Structures’ which in turn is part of the overall uffmm.org Blog.

Preface

In an earlier post the overall structure of the oksimo paradigm has been outlined. This was the perspective available during spring 2021. Since this time the theory, the software as well as the applications are evolving very quickly. A major event was the closer and closer conjunction of a general ’empirical everyday life theory’ [1] with the oksimo paradigm. The central idea is that an oksimo application is by its implicit structure a complete empirical theory in an everyday life setting. This growing clearness about the theoretical dimension of an oksimo application raises new questions how to organize an oksimo application.

Oksimo Workflow

The figure shows the basic oksimo workflow between a user/ group of users and the oksimo simulator (theory inference machine): A user can upload an oksimo simulation (= theory) document to the simulator either by sending an address for an HTML-document or by directly uploading a text document in agreement with a minimal HTML-schema. The upload includes some additional parameters as directives for the wanted format of the output. The simulator computes then the output according to the selected parameters an shows an HTML page either directly on the login page of the simulator or as an HTML document sent to the email address which the user has specified.

In the first software development phase the main interest was the clarification of the concept of a theory-like environment using only everyday language (every language is possible). In the second phase this has been extended by allowing math-extensions to the everyday language accompanied by first simple graphical presentations during the simulation. Oksimo can be used here in single mode as well as in multiple user mode allowing an exchange of data as well as a ‘unification’ of different simulations

This is quite powerful.

But at this point the oksimo paradigm looks a bit like an ‘Island’: living there is OK, but there is not yet some ‘normal exchange’ possible.

Looking back in history Tim Berners-Lee [2] has during his life-time developed the idea of an open space of knowledge and communication embedded in a space called World Wide Wed [WWW]. Despite all the many details there one can see one central idea: an open space of addresses each representing a web-page, which can be a html-page. Thus the WWW can be understood as an universal ‘interface’ between people exchanging knowledge in the format of HTML-pages. And because an HTML-page follows a clearly defined pattern everybody can read and write such html-pages with simple readers and writers.

While the oksimo software itself is for a user available through an interactive web-page and it’s outputs can already be shown on a web-page it is not a too big step to extend the oksimo software generally with an export-function of a simulation as a complete html-page and as well with an import-function read an html-page which contains a complete simulation as a text which then is ‘converted’ in states, goals and rules which are needed for the simulator.

Thus without changing the software as it is now one could make the oksimo software with these additional functions immediately speaking to the whole World Wide Web.

By this step every user in the world wide web could edit a simulation with a normal editor, post this on a server of personal choice for everybody and vice versa every user could read everywhere html-pages with simulations, download them and modify or extend these in the light of his experience. This would enable a new kind of wikipedia-like servers. In this sense the oksimo paradigm could perhaps become the new operating system for the whole knowledge space.[3]

COMMENTS

[1] See the post “POPPER and EMPIRICAL THEORY. A conceptual Experiment” which gives a complete outline of the idea of an empirical everyday life theory.

[2] Tim Berners-Lee, Weaving the Web. The original design and ultimate destiny of the world wide web, HarperCollins Publishers, New York, 1999

[3] This can remind us a bit to the wonderful vision of ‘Collective Intelligence’ described by Pierre Lévy.

OKSIMO APPLICATIONS – Simple Examples – Citizens of a County – Example 2

eJournal: uffmm.org ISSN 2567-6458

30.March 2022 – 31.March 2022, 11:55h
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

BLOG-CONTEXT

This post is part of the Oksimo Application theme which is part of the uffmm blog.

PREFACE

This post shows a continuation from the simple simulation example in the preceding post. It points to an implicit problem of the demographic modeling of the Main-Kinzig County (German: Main-Kinzig Kreis [MKK]) only using the official numbers available in the World Wide Web from the Hessian statistical office. Some questions arise without giving an answer in this post.

A REAL SIMULATION

The following example has been run with Oksimo v2.0 (Pre-Release) (c972). Hopefully we can finish the pre-release to a full release the next few days.

STRUCTURE OF THE SIMULATION

The structure of the simulation follows the schema of an empirical theory as follows:

  1. A ‘given situation’ will be described which is assumed to be ’empirically sound’ by the authors.
  2. A ‘state in the future’ (‘vision’, ‘goal’ ‘forecast’) is given for benchmarking.
  3. At least one ‘change rule’ is given representing an ‘inference rule’ for everyday experience.
  4. The ‘inference engine’ for making a ‘logical deduction’ is ‘hidden’ in the ‘simulator’, which is doing the job of applying the change rules to a given situation.

Here the concrete definitions:

VISION

Name: vmkkdemo1

Expressions:

The Main-Kinzig County exists.

Math expressions:

YEAR>2032

GIVEN STATE

Name: smkkDemo1

Expressions:

The Main-Kinzig County exists.

The number of citizens is known.

Based on preceding years a growth rate could be computed.

A growth rate has two components: natural increase and net migration.

The component natural increase has again two components: the rates of births and deaths.

The net migration is based on rates for immigration and emigrations.

The number for a population in a year t+1 is the product of the population of the preceding year t enriched with the natural increase and the net migration.

Math expressions:

IMMIGRATION=18000Amount

EMIGRATION=15900Amount

NETMIGR=0Number

BIRTHS=59400Amount

DEATHS=70000Amount

NATINCREASE=0Number

CITIZENS=421689Amount

YEAR=2020Number

CHANGE RULE (Inference Rule)

(Attention: There can be arbitrary many rules; here only one is used)

This figure gives a graphical overview of the main parameters used in the demographic modeling below.

Rule name: rworld1

Probability: 1.0

Conditions:

The Main-Kinzig County exists.

Math conditions:

YEAR>=0

Effects plus:

Effects minus:

Effects math:

YEAR=YEAR+1

NETMIGR=IMMIGRATION-EMIGRATION

NATINCREASE=BIRTHS-DEATHS

CITIZENS=CITIZENS+NATINCREASE+NETMIGR

SIMULATION

simmkkDemo2

Selected visions:

vmkkdemo1

Selected states:

smkkDemo1

Selected rules:

rworld1

GRAPH CITIZENS

The figure shows the values of the variable ‘CITIZENS’ during 15 cycles of simulation.

GRAPH NETMIGR NATINCREASE

This figure shows the values of the variables NETMIGR and NATINCREASE. These produce a negative difference which influences the size of the population.

Here the log protocol from simulation cycles 12-13:

Round 12

State rules:
rworld1 applied  (Prob: 100 Rand: 11/100)
Math applied:
CITIZENS=CITIZENS+NATINCREASE+NETMIGR
NATINCREASE=BIRTHS-DEATHS
YEAR=YEAR+1
NETMIGR=IMMIGRATION-EMIGRATION
Vision rules:
Current states: The number of citizens is known.,The component natural increase has again two components: the rates of births and deaths.,The net migration is based on rates for immigration and emigrations.,The Main-Kinzig County exists.,A growth rate has two components: natural increase and net migration.,The number for a population in a year t+1 is the product of the population of the preceding year t enriched with the natural increase and the net migration.,Based on preceding years a growth rate could be computed.
Current visions: The Main-Kinzig County exists.
Current values:
IMMIGRATION: 18000Amount
NETMIGR: 2100Number
BIRTHS: 59400Amount
DEATHS: 70000Amount
NATINCREASE: -10600Number
CITIZENS: 328189Amount
YEAR: 2032Number
EMIGRATION: 15900Amount

50.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
None

Round 13

State rules:
rworld1 applied  (Prob: 100 Rand: 63/100)
Math applied:
CITIZENS=CITIZENS+NATINCREASE+NETMIGR
NATINCREASE=BIRTHS-DEATHS
YEAR=YEAR+1
NETMIGR=IMMIGRATION-EMIGRATION
Vision rules:
Current states: The number of citizens is known.,The component natural increase has again two com
ponents: the rates of births and deaths.,The net migration is based on rates for immigration and 
emigrations.,The Main-Kinzig County exists.,A growth rate has two components: natural increase an
d net migration.,The number for a population in a year t+1 is the product of the population of th
e preceding year t enriched with the natural increase and the net migration.,Based on preceding y
ears a growth rate could be computed.
Current visions: The Main-Kinzig County exists.
Current values:
IMMIGRATION: 18000Amount
NETMIGR: 2100Number
BIRTHS: 59400Amount
DEATHS: 70000Amount
NATINCREASE: -10600Number
CITIZENS: 319689Amount
YEAR: 2033Number
EMIGRATION: 15900Amount

100.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
YEAR>2032

One can see here that the simulator announces a 100% satisfaction of the goal because the year 2032 has been passed and the Main-Kinzig County still exists.

DISCUSSION

Although the shown simulation is still extremely simple it points to a hidden problem of the official demographic data. The hessian statistical office computes a forecast for the MKK in 2040 with 420443 citizens starting with the year 2018. [3] Comparing these numbers with those from the demographic changes between 1.January 2021 and 30.June 2021 [2] then one gets a real difference: NATINCREASE -7.7 becomes -0.15% and NETMIGR 8.0 becomes 0.21%. This results in a 6-month fraction of about -736 to -635 for NATINCREASE and of about 764 to 889 for NETMIGR.

These observations point (i) to the general problem of getting ‘good data’ and (ii) at the same time how fragile the data are. With rather constant rates in births and deaths the migration data can change a lot. For 2020-2021 we have with 2.107 a NETMIGR rate of about 0.5%. [1] What now are the ‘real data’?

A DIFFERENT SIMULATION

Until now we have only data from single points of time (2018, 2021 (2040)) or of a small time window (1.January 2021, 30.June 2021). If we would take the data from the time window (Jan 2021, Jun 2021) and if we take the change rates from these data as percentage of the final value of citizens, then we are producing another graph knowing, that this clearly will not represent ‘the empirical reality’ sufficiently well. Nevertheless it can help to get some ‘awareness’ that the real numbers deserve more research, especially related to their ‘dynamics’ which is embedded in rather complex clusters of different factors interacting with each other.[4]

STRUCTURE OF SIMULATION

GIVEN SITUATION

TEXT

Name: smkkDemo2

The Main-Kinzig County exists.

The number of citizens is known.

Based on preceding years a growth rate could be computed.

A growth rate has two components: natural increase and net migration.

The component natural increase has again two components: the rates of births and deaths.

The net migration is based on rates for immigration and emigrations.

The number for a population in a year t+1 is the product of the population of the preced

ing year t enriched with the natural increase and the net migration.

Math:

NETMIGR=0Number

NATINCREASE=0Number

YEAR=2020Number

IMMIGRATION=0Amount

EMIGRATION=0Amount

BIRTHS=0Amount

DEATHS=0Amount

CITIZENS=421689Amount

POSSIBLE VISION (GOAL)

TEXT

Name: vmkkdemo1

Expressions:

The Main-Kinzig County exists.

Math expressions:

YEAR>2040

CHANGE RULES

Rule name: rworld2

Probability: 1.0

Conditions:

The Main-Kinzig County exists.

Math conditions:

YEAR>=0

Effects plus:

Effects minus:

Effects math:

YEAR=YEAR+1

BIRTHS=CITIZENS*0.0046

DEATHS=CITIZENS*0.006

EMIGRATION=CITIZENS*0.029

IMMIGRATION=CITIZENS*0.03

Rule name: rworld2b

Probability: 1.0

Conditions:

The Main-Kinzig County exists.

Math conditions:

YEAR>=0

Effects plus:

Effects minus:

Effects math:

NATINCREASE=BIRTHS-DEATHS

NETMIGR=IMMIGRATION-EMIGRATION

Rule name: rworld3

Probability: 1.0

Conditions:

The Main-Kinzig County exists.

Math conditions:

YEAR>=0

Effects plus:

Effects minus:

Effects math:

CITIZENS=CITIZENS+NATINCREASE+NETMIGR

SIMULATION

simmkkDemo3

Selected visions:

vmkkdemo1

Selected states:

smkkDemo2

Selected rules:

rworld2

rworld2b

rworld3

GRAPH CITIZENS

This figure shows the decreasing number of citizens in the county which is due to the fact that the NATINCR is bigger than the NETMIGR. But one has to keep in mind, that dies reflects the values from the first 6 months from the year 2021. These values can change, but HOW will these values change? What are the empirical factors which do influence these values?

GRAPH NATINCR and NETMIGR

Here the nearly constant values of NATINCR and NETMIGR taken from the year 2021

Here cycles 1-2 from the simulation log:

Round 1

State rules:
rworld2 applied  (Prob: 100 Rand: 40/100)
Math applied:
IMMIGRATION=CITIZENS*0.03
YEAR=YEAR+1
DEATHS=CITIZENS*0.006
BIRTHS=CITIZENS*0.0046
EMIGRATION=CITIZENS*0.029
rworld3 applied  (Prob: 0 Rand: 58/100)
Math applied:
CITIZENS=CITIZENS+NATINCREASE+NETMIGR
rworld2b applied  (Prob: 100 Rand: 6/100)
Math applied:
NATINCREASE=BIRTHS-DEATHS
NETMIGR=IMMIGRATION-EMIGRATION
Vision rules:
Current states: The number for a population in a year t+1 is the product of the population of the preceding year t enriched with the natural increase and the net migration.,The net migration is based on rates for immigration and emigrations.,The component natural increase has again two components: the rates of births and deaths.,The Main-Kinzig County exists.,A growth rate has two components: natural increase and net migration.,Based on preceding years a growth rate could be computed.,The number of citizens is known.
Current visions: The Main-Kinzig County exists.
Current values:
NETMIGR: 421.6890000000003Number
NATINCREASE: -590.3646000000001Number
YEAR: 2021Number
IMMIGRATION: 12650.67Amount
EMIGRATION: 12228.981Amount
BIRTHS: 1939.7694Amount
DEATHS: 2530.134Amount
CITIZENS: 421689Amount

50.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
None

Round 2

State rules:
rworld3 applied  (Prob: 0 Rand: 95/100)
Math applied:
CITIZENS=CITIZENS+NATINCREASE+NETMIGR
rworld2 applied  (Prob: 100 Rand: 22/100)
Math applied:
IMMIGRATION=CITIZENS*0.03
YEAR=YEAR+1
DEATHS=CITIZENS*0.006
BIRTHS=CITIZENS*0.0046
EMIGRATION=CITIZENS*0.029
rworld2b applied  (Prob: 100 Rand: 32/100)
Math applied:
NATINCREASE=BIRTHS-DEATHS
NETMIGR=IMMIGRATION-EMIGRATION
Vision rules:
Current states: The number for a population in a year t+1 is the product of the population of the preceding year t enriched with the natural increase and the net migration.,The net migration is based on rates for immigration and emigrations.,The component natural increase has again two components: the rates of births and deaths.,The Main-Kinzig County exists.,A growth rate has two components: natural increase and net migration.,Based on preceding years a growth rate could be computed.,The number of citizens is known.
Current visions: The Main-Kinzig County exists.
Current values:
NETMIGR: 421.5203243999986Number
NATINCREASE: -590.1284541600003Number
YEAR: 2022Number
IMMIGRATION: 12645.609732Amount
EMIGRATION: 12224.089407600002Amount
BIRTHS: 1938.9934922400003Amount
DEATHS: 2529.1219464000005Amount
CITIZENS: 421520.32440000004Amount

50.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
None

And here the the cycles 20-21 showing 100% success

Round 20

State rules:
rworld2b applied  (Prob: 100 Rand: 78/100)
Math applied:
NATINCREASE=BIRTHS-DEATHS
NETMIGR=IMMIGRATION-EMIGRATION
rworld3 applied  (Prob: 0 Rand: 90/100)
Math applied:
CITIZENS=CITIZENS+NATINCREASE+NETMIGR
rworld2 applied  (Prob: 100 Rand: 20/100)
Math applied:
IMMIGRATION=CITIZENS*0.03
YEAR=YEAR+1
DEATHS=CITIZENS*0.006
BIRTHS=CITIZENS*0.0046
EMIGRATION=CITIZENS*0.029
Vision rules:
Current states: The number for a population in a year t+1 is the product of the population of the preceding year t enriched with the natural increase and the net migration.,The net migration is based on rates for immigration and emigrations.,The component natural increase has again two components: the rates of births and deaths.,The Main-Kinzig County exists.,A growth rate has two components: natural increase and net migration.,Based on preceding years a growth rate could be computed.,The number of citizens is known.
Current visions: The Main-Kinzig County exists.
Current values:
NETMIGR: 418.83020290706736Number
NATINCREASE: -586.3622840698965Number
YEAR: 2040Number
IMMIGRATION: 12554.852151152843Amount
EMIGRATION: 12136.35707944775Amount
BIRTHS: 1925.077329843436Amount
DEATHS: 2510.9704302305686Amount
CITIZENS: 418495.0717050948Amount

50.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
None

Round 21

State rules:
rworld2 applied  (Prob: 100 Rand: 16/100)
Math applied:
IMMIGRATION=CITIZENS*0.03
YEAR=YEAR+1
DEATHS=CITIZENS*0.006
BIRTHS=CITIZENS*0.0046
EMIGRATION=CITIZENS*0.029
rworld2b applied  (Prob: 100 Rand: 28/100)
Math applied:
NATINCREASE=BIRTHS-DEATHS
NETMIGR=IMMIGRATION-EMIGRATION
rworld3 applied  (Prob: 0 Rand: 41/100)
Math applied:
CITIZENS=CITIZENS+NATINCREASE+NETMIGR
Vision rules:
Current states: The number for a population in a year t+1 is the product of the population of the preceding year t enriched with the natural increase and the net migration.,The net migration is based on rates for immigration and emigrations.,The component natural increase has again two components: the rates of births and deaths.,The Main-Kinzig County exists.,A growth rate has two components: natural increase and net migration.,Based on preceding years a growth rate could be computed.,The number of citizens is known.
Current visions: The Main-Kinzig County exists.
Current values:
NETMIGR: 418.49507170509423Number
NATINCREASE: -585.8931003871326Number
YEAR: 2041Number
IMMIGRATION: 12554.852151152843Amount
EMIGRATION: 12136.35707944775Amount
BIRTHS: 1925.077329843436Amount
DEATHS: 2510.9704302305686Amount
CITIZENS: 418327.6736764127Amount

100.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
YEAR>2040,

Special Comments to the Software

As mentioned in the beginning the version of the software used here is not yet the final one. We are still in an ‘experimental phase’. A feature we detected dealing with this simulation is that the simulator takes all ‘elements’ of the ‘effect part’ of a rules as ‘equal’, not applying some order for the execution. In the case of math expressions which have ‘internally’ some ‘logical order’ in the sense, that an expression A presupposes an expression B to be computed ‘before’ the expression A has to be computed (which is in this simulation clearly the case), one can handle this only if one locates all math expressions which belong to ‘the same logical level’ into a separate rule. We have to have a look to this. In such a case ‘theory’ is interacting with ‘implementation details’ which follow a quite different logic.

COMMENTS

[1] Matrix of the Immigration and Emigration of citizens between the different cities and counties of the state of Hessen in 2020, Hess.Statistisches Landesamt: https://statistik.hessen.de/zahlen-fakten/bevoelkerung-gebiet-haushalte-familien/bevoelkerung/tabellen

Figure shows the matrix of all immigrations and emigrations between the cities and counties of the state of Hessen in 2020. For the MKK county we have Going-Out= 15.903 and Coming-In=18.010, which represents about 0.5% NETMIGR in 2020-2021.

[2] Demographic Changes between 1.January 2021 and 1.June 2021 for the MKK county, in: https://statistik.hessen.de/sites/statistik.hessen.de/files/AI2_AII_AIII_AV_21-1hj.pdf. p.7

This shows the number of citizens in the MKK county 1.January 2021 with 421.689 and 30.June 2021 with 421.936. The other variables are BIRTHs=1.942, DEATHs=2.577, IMMIGRANTS=12950, EMIGRANTS=12.061. This yields a NATINCREASE=BIRTHS-DEATHS = -635, NETMIGR=IMMIGRANTS-EMIGRANTS= 889. This points to a NATINCREASE of -0.15% and a NETMIGR of 0.21%, which gives an overall increase of 0.06%.

[3] Demographic Forecast for the years 2040, Hess.Statistisches Landesamt: https://statistik.hessen.de/zahlen-fakten/bevoelkerung-gebiet-haushalte-familien/bevoelkerung/tabellen

Figure shows the forecast for the Main-Kinzig County for the year 2040. If one compares these numbers with the ‘more real data’ of those in [2] then we see the following changes: NATINCREASE -7.7 becomes -0.15% and NETMIGR 8.0 becomes 0.21%. This results in a 6-month fraction of about -736 to -635 for NATINCREASE and of about 764 to 889 for NETMIGR.

[4] In the first paper of the small booklet from Karl Popper, „A World of Propensities“, Thoemmes Press, Bristol, (1990, repr. 1995), he develops the idea of associating an observable phenomenon with some part of the real world which has to be assumed as necessary environment for a phenomenon to be able to appear. And this presupposed empirical environment is always a complex cluster of different empirical factors interacting with each other and thereby are ‘causing’ phenomena which are not traceable to only one factor in a deterministic way but to ‘many’. ‘Chance’ is therefore a ‘product’ of reality not an isolated single event.

OKSIMO APPLICATIONS – Simple Examples – Citizens of a County

eJournal: uffmm.org ISSN 2567-6458

27.March 2022 – 27.March 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

BLOG-CONTEXT

This post is part of the Oksimo Application theme which is part of the uffmm blog.

PREFACE

This post shows a simple simulation example with the beta-version of the new Version 2 of the oksimo programming environment. This example shall illustrate the concept of an ‘Everyday Empirical Theory‘ as described in this blog 11 days before. It is intentionally as ‘simple as possible’. Probably some more examples will be shown.

FROM THEORY TO AN APPLICATION

To apply a theory concept in an everyday world there are many formats possible. In this text it will be shown how such an application would look like if one is applying the oksimo programming environment. Until now there exists only a German Blog (oksimo.org) describing the oksimo paradigm a little bit. But the examples there are written with oksimo version 1, which didn’t allow to use math. In version 2 this is possible, accompanied by some visual graph features.

Everyday Experts – Basic Ideas

This figure shows a simple outline of the basic assumptions of the oksimo programming environment constituting the oksimo paradigm: (i) Every human person is assumed to be a ‘natural expert’ being member of a bigger population which shares the same ‘everyday language’ including basic math. (ii) An actor is embedded in some empirical environment including the own body and other human actors. (iii) Human actors are capable of elaborating as inner states different kinds of ‘mental (cognitive) models’ based on their experience of the environment and their own body. (iv) Human actors are further capable to use symbolic languages to ‘represent’ properties of these mental models encoded in symbolic expressions. Such symbolic encoding presupposes an ‘inner meaning function’ which has to be learned. (v) In the oksimo programming environment one needs for the description of a ‘given state’ two kinds of symbolic expressions: (v.1) Language expressions to describe general properties and relations which are assumed to be ‘given’ (= ‘valid by experience’); (v.2) Language expressions to name concrete quantitative properties (simple math expressions).

This figure shows the idea how to change a given state (situation) by so-called ‘change rules’. A change rule encodes experience from the everyday world under which conditions some properties of a given situation S can be ‘changed’ in a way, that a ‘new situation’ S* comes into being. Generally a given state can change if either language expression is ‘deleted’ from the description or ‘contributed’. Another possibility is realized if one of the given quantitative expressions changes its value. In the above simple situation the only change happens by changing the number of citizens by some growth effect. But, as other examples will demonstrate, everything is possible what is possible in the empirical world.

SOME MORE FEATURES

The basic schema of the oksimo paradigm assumes the following components:

  1. The description of a ‘given situation’ as a ‘start state’.
  2. The description of a ‘vision’ functioning as a ‘goal’ which allows a basic ‘Benchmarking’.
  3. A list of ‘change rules’ which describe the assumed possible changes
  4. An ‘inference engine’ called ‘simulator’: Depending from the number of wanted ‘simulation cycles’ (‘inferences’) the simulator applies the change rules onto a given state S and thereby it is producing a ‘follow up state’ S*, which becomes the new given state. The series of generated states represents the ‘history’ of a simulation. Every follow up state is an ‘inference’ and by definition also a ‘forecast’.

All these features (1) – (4) together constitute a full empirical theory in the sense of the mentioned theory post before.

Let us look to a real simulation.

A REAL SIMULATION

The following example has been run with Oksimo v2.0 (Pre-Release) (353e5). Hopefully we can finish the pre-release to a full release the next few weeks.

A VISION

Name: v2026

Expressions:

The Main-Kinzig County exists.

Math expressions:

YEAR>2025 and YEAR<2027

This simple goal assumes the existence of the Main-Kinzig County for the year 2026.

GIVEN START STATE

Name: StartSimple1

Expressions:

The Main-Kinzig County exists.

The number of citizens is known.

Comparing the number of different years one has computed a growth rate.

Math expressions:

YEAR=2018Number

CITIZENS=418950Amount

GROWTH=0.0023Percentage

The start state makes some simple statements which are assumed to be ‘valid’ in a ‘real given situation’ by the participating natural experts.

CHANGE RULES

In this example there is only one change rules (In principle there can be as many change rules as wanted).

Rule name: Growth1

Probability: 1.0

Conditions:

The Main-Kinzig County exists.

Math conditions:

CITIZENS < 450000

Effects plus:

Effects minus:

Effects math:

CITIZENS=CITIZENS+(CITIZENS*GROWTH)

YEAR=YEAR+1

This change rules is rather simple. It looks only to the fact whether the Main-Kinzig County exists and wether the number of citizens is still below 450000. If this is the case, then the year will be incremented and the number of citizens will be incremented according to an extremely simple formula.

For every named quantity in this simulation (YEAR, GROWTH, CITIZENS) the values are collected for every simulation cycle and therefore can be used for evaluations. In this simple case only the quantities of YEAR and CITIZENS have changes:

Simple linear graph for the quantity named YEAR
Simple linear graph for the quantity named CITIZENS

Here the quick log of simulation cycle round 7 – 9:

Round 7

State rules:
Vision rules:
Current states: The number of citizens is known.,Comparing the number of different years one has computed a growth rate.,The Main-Kinzig County exists.
Current visions: The Main-Kinzig County exists.
Current values:
YEAR: 2025Number
CITIZENS: 425741.8149741673Amount
GROWTH: 0.0023Percentage

50.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
None

Round 8

State rules:
Vision rules:
Current states: The number of citizens is known.,Comparing the number of different years one has computed a growth rate.,The Main-Kinzig County exists.
Current visions: The Main-Kinzig County exists.
Current values:
YEAR: 2026Number
CITIZENS: 426721.0211486079Amount
GROWTH: 0.0023Percentage

100.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
YEAR>2025 and YEAR<2027,

Round 9

State rules:
Vision rules:
Current states: The number of citizens is known.,Comparing the number of different years one has computed a growth rate.,The Main-Kinzig County exists.
Current visions: The Main-Kinzig County exists.
Current values:
YEAR: 2027Number
CITIZENS: 427702.4794972497Amount
GROWTH: 0.0023Percentage

50.00 percent of your vision was achieved by reaching the following states:
The Main-Kinzig County exists.,
And the following math visions:
None

In round 8 one can see, that the simulation announces:

100.00 percent of your vision was achieved by reaching the following states: The Main-Kinzig County exists., And the following math visions: YEAR>2025 and YEAR<2027

From this the natural expert can conclude that his requirements given in the vision are ‘fulfilled’/’satisfied’.

WHAT COMES NEXT?

In a loosely order more examples will follow. Here you find the next one.

Pierre Lévy : Collective Intelligence – Chapter 7 – The Four Spaces

eJournal: uffmm.org, ISSN 2567-6458,
24.March 2022 – 6.April 2022, 08:04 h
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

SCOPE

In the uffmm review section the different papers and books are discussed from the point of view of the oksimo paradigm. [1] In the following text the author discusses chapter 7 of the book “Collective Intelligence. mankind’s emerging world in cyberspace” by Pierre Lévy (translated by Robert Bonono),1997 (French: 1994)[2]

CONTEXT

In a proceeding post the general idea of the book of Lévy has been discussed. The final impression was, that Lévy’s vision of collective intelligence embedded in the development of human culture shows a high agreement with the oksimo paradigm of the author of this text. Reading continuous with some more chapters of the book. It starts with chapter 7, the beginning of Part II of the book

Chapter 7: The Four Spaces

POSITION LÉVY

In this chapter Lévy is bringing back some ideas of chapter 1, pp.5-10, where he did a partitioning of the timeline of the development of life on earth according to some criteria. The main topics are ‘Earth’, ‘Territory’, ‘Commodity Space’, and ‘Knowledge Space’.

Earth

Beginning his selected timeline with the advent of humanity on earth Lévy describes in a short but highly dense text (cf. p.131f) his view of the interaction of humankind with the earth, which appears for him as an all embracing permanence, without origin, not a small ecological niche, but a ‘cosmos’ with stars, imagined gods, freely envisioned ancestors, continuously re-creating the experience of the earth with signs, languages, tales, rituals, and tools. The realness of the earth is mixed up with human emotions, dreams and fantasies and thereby allowing some transcendence being an inner dimension of the all embracing earth-humankind experience.

Territory

Whenever humanity appeared in the history of life on this planet, for the last 12.000 years Lévy sees for these times a phenomenon called ‘territory’.(cf. p.133) The unbounded experience of an unlimited ‘cosmos’ reverberating in every human individual becomes ‘structured’ by a more organized environment by ‘real things’ and ‘new forms of the social bond’. Here ‘civilization’ begins: “… rearing of animals, agriculture, the city and state, writing, the strict social division of labor, ..”(p.133) Although one can say that the territory “dominates, confines, encloses, describes, and measures it [the earth?]”(p.134), the unconfined earth has not disappeared, it always strikes back providing an ever continuing conflict.(cf. p.134) During this Neolithic period [3] the new reality reverberated not only to the individual, but “to the great social machine, to the state.”(p.134) In this time the majority of humanity “were peasants who inhabited the territory.”(p.135)

Commodity Space

After ‘earth’ and ‘territory’ as as form-factors of society and the reverberating mind Lévy sees then a next big modification in the cultural patterns of humanity which he circumscribes as ‘commodity space’ [4].(cf. pp.135-138) He characterizes this new mode by a statement like this: “… but a new world built from the incessant circulation of money in an ever tightening, ever quickening loop.”(p.135) And he continuous: “Crossing borders, upsetting territorial hierarchies, the dance of money brought in its wake an accelerated movement, a rising tide of objects, signs, and individuals.”(p.136) And Lévy sees a close relationship between this new commodity space and ‘capitalism’, which “draws everything in its orbit” (p.136) Associated with the wake of science, technology and the flux of signs everything is becoming changeable by reinterpretation, constructible by technology, and exchangeable by money. The old Neolithic territory is mixing up with these new forms of interactions and transactions making Capitalism with industry and commerce the “principal engines driving the evolution of human societies.”(p.137) For Lévy is capitalism the main factor: “… the great cybernetic machine of capital … seems invincible, inexhaustible. Capitalism is irreversible. It is economy and has made economy the permanent dimension of human existence.”(p.137)

Knowledge Space

In this chapter the imaginative power of Lévy’s language which encloses the reader all the time comes to an intensity wich is hardly to surpass. Between statements like “The knowledge space doesn’t exist” (p.138) and “The knowledge space has always existed” (p.139) he is practicing a kind of ‘conjuring up’ something, which is there and is not, not in the usual sense. For Lévy ‘knowledge’ is “not simply scientific knowledge” (p.139) and it “can’t be reduced to so-called rational discourse.” (p.139)

The knowledge conjured up here is something which “qualifies our species, Homo sapiens.”(p.139) It “is a knowledge-of-living, a living-in-knowledge, one that is coextensive with life. It is part of a cosmopolitan and borderless space of relations and qualities, a space for the metamorphosis of relationships and the emergence of ways of being, a space in which the processes of individual and collective subjectivization come together.” (p.139) This knowledge follows a “virtual emergence”. (p.139) But, as such, the knowledge space “is not a return to earth, but a return of the earth to itself, an overflight of the earth by itself at the speed of light, an uncontrolled cosmic diversification.”(p.141)

COMMENTS ON LÉVY

Here some comments on the position of Lévy.

Comments on ‘Earth’

Already in this short text of Lévy, in his mental reconstruction of a time which has passed long ago, one can ‘sense’ a basic dynamic structure which allows a permanent interaction of human actors, human populations with the real earth and with each other. But this richness of behavior, these varieties of effects are only indicators of a fascinating ‘inner structure’ of human actors, which does not appear as a ‘dead object’ but as some new kind of living: the impressions of the world are becoming ‘transformed’ in multiple ways individually but also by social entanglements. The symbolic spaces function as a medium, like a catalyst, allowing transformations in the mental-cognitive space, which are steering the public behavior and by resonance they feed back into this inner dynamics of a symbolically mediated world-mind. There is a continuing process of the real world interacting with a distributed mind world. And this distributedness of a real world by a minded world is not fixed to one individual human actor alone but is present in all the members of a group, a population by understanding, by talking, by acting. This distributed manifestation of a symbolic mind world enables a ‘new reality’, a ‘cognitively mediated real world’, a true ‘virtual world’ as the primary world in the inner dynamics of every human actor.

Comments on ‘Territory’

Lévy continues with his dense descriptions of the changing behaviors and social patterns manifested by humanity spreading over the surface of the earth. The growing number of members of groups, tribes which are using more and more the advantages of special territories, of special tools and procedures, of new formats of social bonds. But he does not dig into the ‘inner reality’ of individual and distributed minds, which function as the ‘soul’ of these new social machines, the new ‘states’. With the ‘change’ in the format of the environment perception, mwithemorizing, thinking inevitably is changing too. And the connecting language with their adapted meanings is mimicking these changes in many details. Thus the changes of the ‘outer environment’ are reverberating inside and inducing an inner cognitive-mental world, a ‘true virtual reality’, which functions as the ‘primary picture of the world’, a ‘distributed’ one. If some individual ‘fails’, if it ‘dies away’, the ‘distributed inner world’ will not change: it ‘preserves itself’ and ‘feeds back’ to all individuals of the society as the ‘given norm’. The real world is touching us as a ‘particular’ experience, but the ‘distributed inner world’ is a ‘network of associations’, an ‘informed whole picture’, giving ‘sense to each part by this inner connectedness’. The writing is an invaluable tool to support parts of this distributed inner world to be kept, be memorized.

As the environmental ‘properties and structures’ are being transformed into new social-cultural patterns and the distributed thinking is ‘absorbing’ these, then the ‘distributed inner pictures’ will ‘overwrite’ the world ‘behind the daily experiences’. Humankind in a city has no longer an idea of a world without a city. Collective intelligence generates its own ‘mental gravity’. Negatively this is a kind of a ‘locked-in syndrome’. If the ‘distributed mental models’ enable some more ‘deep-sighted’ or ‘far-sighted’ perspectives supporting ‘survival in the future’ then it can be ‘positive’, a ‘constructive locked-in syndrome’. But this variety of a ‘locked-in collective intelligence’ is constantly in danger to ‘believe more in itself’ than to the ‘world talking by partial experience’.

Comments on Commodity Space

The suggestive spirit of Lévy’s description of the commodity space is strong. Indeed, it looks like a hidden power which moves everything in new combinations, new orders, new interpretations, mostly associated with money and power. The installation of new forms of interactions and transactions crossing classical borders of territories like birds in the air appears to transcend the old world of territories. Values seem now to be able to live everywhere, owned by everybody, changing everything.

Comparing these cultural patterns to those of non-human biological species reveals that these new phenomena are indeed not ‘in the air’, they are rooted in the special capabilities of human persons and their new forms of cooperation by communication, enabling the spreading of new ideas rooted in the brains of individual bodies. Cutting the communication would disable ideas of being spread, would enclose ideas ‘in itself’, nothing would be possible.

Modern societies which systematically are suppressing public communication supporting only special opinions practicing a modified form of cutting communication and they show weak forms of disintegration of knowledge and cultural behavior.

Thus ‘capitalism’ and associated forms of ‘economy’ are not complete ‘autonomous phenomena’ but are presupposing certain kinds of communication mediating certain kinds of ideas which influence the behavior. And this ‘behavior of individuals’ is driven by different kinds of ideas, emotions, and desires. Those ideas which seem to ‘support’ capitalism and associated forms of economy are not ‘absolute’ ideas, not ‘inborn’ ideas; therefore these ideas can be changed, can be ‘improved’ and thereby they can — in principle — change behavior and thereby they can change the whole culture. And, besides this, the reality of the cosmos, of the planet earth and the biosphere, which is a ‘given’ reality, follows its own ‘independent logic’ and can lead to a ‘crash’ with a culture, which is ‘too far away’ from this empirical reality.

Comments on Knowledge Space

As stated above, Lévy’s language is impressive, dense, poetic. To some extend this is triggered by the kind of appearance how the knowledge space is given and not given. He stresses several times that the other mentioned anthropological spaces — Earth, Territory, and Commodities — are not vanishing; they are still there, stay in existence with all their real power, but the knowledge space is somehow different, somehow new, is nevertheless also there, ‘not unreal’, ‘virtual’, ‘in between’, subjective but at the same time ‘collective’.

As mentioned in preceding comments what is – in my understanding — missing in Lévy’s wonderful tale is the ‘anatomy of the virtual in realness’. As we know from an individual homo sapiens exemplar it has a ‘real body’, but inside this body there are ‘inner processes’ which as processes are still ‘real’, but these processes are constituting a complex network of inner states which are ‘mapping each other to each other’. Small parts of this ‘self-mapping’ are know as ‘consciousness’, and ‘self-consciousness’. Real structures (neurons, brain) are setting up relations which as such are again ‘mapped’ to other structures and thereby building up an ‘inner semantic space’ which allows the ‘re-imagination’ of signals from the ‘outer world’ which we assume as ‘real’ like our own body.

This inner semantic space of a single brain already commands ‘now’ and ‘past’, concrete versus abstract, associations, arrangements, playing with combinations, embedded always in emotions, feelings, drives. The ‘virtual’ compared to the assumed outer world is here ‘the real’, that, what is going on.

And already with the presence of the homo sapiens population with interactions there exists between homo sapiens exemplars a communication, enriched with symbolic languages, which makes every individual to a ‘part of a whole’, which is reverberating also in the inner spaces of everybody. This ‘being part of a whole’ being reflected in the individual inner spaces induces a ‘knowledge space’ right from the beginning which is (virtually) real but not real like the surrounding bodies; the knowledge space is part of oneself (part of the own ‘identity’), but it is not a real-real object but a real-virtual one.

With the emergence of new cultural technologies — writing, books, libraries, computers, computer networks, etc. — it is possible that a human population extends its symbolic space into a partially mechanized symbolic space with new kinds of ‘processes’ dealing with symbols. From the outside it can be (miss)understood as if the semantic space has been de-coupled from the individual members of the knowledge space and can be processed without the individual members. The vision of ‘intelligent machines’ is rising with wild fantasies that this kind of machines can overtake the role of humankind in the long run.

A simple closer look to the ‘anatomy of the virtual being real’ can show that the ‘power of a common language’ is completely rooted in the machinery of a brain in a body. All kinds of ‘meaning’ exist only in these ‘inner mappings’ of neurons onto neurons, where one part of the neurons delivers ‘signals of the outer body world and the own body’ and the other part of the neurons is processing these signals in complex dynamics structures representing somehow the implicit structures of the ‘primary signals’. Because these mapping-processes, this kind of ‘encoding’, is not deterministic but radically ‘adaptive’ in a non-deterministic way, it is completely impossible to substitute this multidimensional dynamic space of possible meanings by secondary processes bounded to symbols alone. What these so-called data-driven artificial machine-learning processes can ‘grasp’ as ‘meaning’ are only some ‘shadows of meaning’ implicitly causing some ‘orders’ in the set of symbols. But ‘some order’ is not ‘meaning’ in the original sense.

Thus a further development of the knowledge space rooted in the huge set of brains coupled by communication and reinforced by virtual echoes of the whole in the individual can only improve if the mechanization of the symbol space by machines keeps a close contact to the original meanings located in the individual brains. Such a ‘contact’ must be ‘real’, must be entangled with the human interactions in a way, which enables a new symbiosis of human mind and mechanized symbol spaces. The today man-machine interfaces are mainly wrong because their design is not guided by a true vision of the human rooted knowledge space but by simple machine metaphors which do not match with a truly knowledge space.

The wonderful picture of Lévy, given in the idea that the knowledge space “is not a return to earth, but a return of the earth to itself” is true in the light of the paradigm of the biosphere which by evolution has ‘brought into being’ biological structures of ‘internal self-mappings’ which allow a biological system, a ‘system of life’, to ‘think virtually’ about alternatives of the now, to think virtually about appearing ‘patterns of the real’, about ‘what it is what there is’ and much more. In this sense is humankind the maximum action of life itself onto life, onto earth, onto the whole universe. But, again, this new dimension of life, the true knowledge space, is not something ‘in the air’, it is a ‘radically real process’ which only can work if the ‘real conditions’ are satisfied. We have to do a ‘real job’ to become more ‘universal’.

OTHER COMMENTS

[1] Gerd Doeben-Henisch,The general idea of the oksimo paradigm: https://www.uffmm.org/2022/01/24/newsletter/, January 2022

[2] Pierre Lévy in wkp-en: https://en.wikipedia.org/wiki/Pierre_L%C3%A9vy

[3] Neolithic period in wkp-en: https://en.wikipedia.org/wiki/Neolithic

[4] Commodity in wkp-en: https://en.wikipedia.org/wiki/Commodity

Pierre Lévy : Collective Intelligence –Footnote: Knowledge Tree

eJournal: uffmm.org, ISSN 2567-6458, 18.March 2022 – 18.March 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

SCOPE

In the uffmm review section the different papers and books are discussed from the point of view of the oksimo paradigm. [1] In this text the author has a small comment to a footnote in the introduction of the book “Collective Intelligence. mankind’s emerging world in cyberspace” by Pierre Lévy (translated by Robert Bonono),1997 (French: 1994)[2]

Footnote: Knowledge Tree and ‘A Blog, not a Book’

The starting page of the uffmm-Blog begins with some philosophical remarks titled ‘A Blog – Not Book’.

At the time of writing these remarks about the character of Blog-Writing the author did not yet know the wonderful book of Pierre Lévy about ‘Collective Intelligence’. Although the whole book can be related to the special idea of Blog-Writing, the author encountered during his reading of the book an interesting footnote no.5 in the introduction of the book.

Graphical interpretation of footnote 5 of the Introduction of the book of Lévy. The subject there is ‘Knowledge Tree’.

The basic idea sees a group of experts with different skills, resulting from different learning processes, which can be projected in real-time into a dynamic knowledge tree showing the individual profiles as well as the landscape of a whole group. This allows many interesting evaluations serving as a constant feedback to improve the individual skills.

Comments

[1] Gerd Doeben-Henisch,The general idea of the oksimo paradigm: https://www.uffmm.org/2022/01/24/newsletter/, January 2022

[2] Pierre Lévy in wkp-en: https://en.wikipedia.org/wiki/Pierre_L%C3%A9vy

Pierre Lévy : Collective Intelligence – Chapter 1 – Introduction

eJournal: uffmm.org, ISSN 2567-6458, 17.March 2022 – 22.March 2022, 8:40
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

SCOPE

In the uffmm review section the different papers and books are discussed from the point of view of the oksimo paradigm. [1] In the following text the author discusses some aspects of the book “Collective Intelligence. mankind’s emerging world in cyberspace” by Pierre Lévy (translated by Robert Bonono),1997 (French: 1994)[2]

PREVIEW

Before starting a more complete review here a notice in advance.

Only these days I started reading this book of Pierre Lévy after working more than 4 years intensively with the problem of an open knowledge space for everybody as genuine part of the cyberspace. I have approached the problem from several disciplines culminating in a new theory concept which has additionally a direct manifestation in a new kind of software too. While I am now are just testing version 2 of this software and having in parallel worked through several papers of the early, the middle, and the late Karl Popper [3], I detected this book of Lévy [*] and was completely impressed by the preface of this book. His view of mankind and cyberspace is intellectual deep and a real piece of art. I had the feeling that this text could be without compromise a direct preview of our software paradigm although I didn’t know about him before.

Looking to know more about him I detected some more interesting books but especially also his blog intlekt – metadata [4], where he develops his vision of a new language for a new ‘collective intelligence’ being practiced in the cyberspace. While his ideas about ‘collective intelligence’ associated with the ‘cyberspace’ are fascinating, it appears to me that his ideas about a new language are strongly embedded in ‘classical’ concepts of language, semiotics, and computer, concepts which — in my view — are not sufficient for a new language enabling collective intelligence.

Thus it can become an exciting reading with continuous reflections about the conditions about ‘collective intelligence’ and the ‘role of language’ within this.

Chapter 1: Introduction

Position lévy

The following description of the position of Lévy described in his 1st chapter is clearly an ‘interpretation’ from the ‘viewpoint’ of the writer at this time. This is more or less ‘inevitable’. [5]

A good starting point for the project of ‘understanding the book’ seems to be the historical outline which Lévy gives on the pages 5-10. Starting with the appearance of the homo sapiens he characterizes different periods of time with different cultural patterns triggered by the homo sapiens. In the last period, which is still lasting, knowledge takes radical new ‘forms’; one central feature is the appearance of the ‘cyberspace’.

Primarily the cyberspace is ‘machine-based’, some material structure, enhanced with a certain type of dynamics enabled by algorithms working in the machine. But as part of the cultural life of the homo sapiens the cyberspace is also a cultural reality increasingly interacting directly with individuals, groups, institutions, companies, industry, nature, and even more. And in this space enabled by interactions the homo sapiens does not only encounter with technical entities alone, but also with effects/ events/ artifacts produced by other homo sapiens companions.

Lévy calls this a “re-creation of the social bond based on reciprocal apprenticeship, shared skills, imagination, and collective intelligence.” (p.10) And he adds as a supplement that “collective intelligence is not a purely cognitive object.” (p.10)

Looking into the future Lévy assumes two main axes: “The renewal of the social bond through our relation to knowledge and collective intelligence itself.” (p.11)

Important seems to be that ‘knowledge’ is also not be confined to ‘facts alone’ but it ‘lives’ in the reziproke interactions of human actors and thereby knowledge is a dynamic process.(cf. p.11) Humans as part of such knowledge processes receive their ‘identities’ from this flow. (cf. p.12) One consequence from this is “… the other remains enigmatic, becomes a desirable being in every respect.”(p.12) With some further comment: “No one knows everything, everyone knows something, all knowledge resides in humanity. There is no transcendent store of knowledge and knowledge is simply the sum of what we know.”(p.13f)

‘Collective intelligence’ dwells nearby to dynamic knowledge: “The basis and goal of collective intelligence is the mutual recognition and enrichment of individuals rather than the cult of fetishized or hypostatized communities.”(p.13) Thus Lévy can state that collective intelligence “is born with culture and growth with it.”(p.16) And making it more concrete with a direct embedding in a community: “In an intelligent community the specific objective is to permanently negotiate the order of things, language, the role of the individual, the identification and definition of objects, the reinterpretation of memory. Nothing is fixed.”(p.17)

These different aspects are accumulating in the vision of “a new humanism that incorporates and enlarges the scope of self knowledge into a form of group knowledge and collective thought. … [the] process of collective intelligence [is] leading to the creation of a distinct sense of community.”(p.17)

One side effect of such a new humanism could be “new forms of democracy, better suited to the complexity of contemporary problems…”.(p.18)

First COMMENTS

At this point I will give only some few comments, waiting with more general and final thoughts until the end of the reading of the whole text.

Shortened Timeline – Wrong Picture

The timeline which Lévy is using is helpful, but this timeline is ‘incomplete’. What is missing is the whole time ‘before’ the advent of the homo sapiens within the biological evolution. And this ‘absence’ hides the understanding of one, if not ‘the’, most important concept of all life, including the homo sapiens and its cultural process.

This central concept is today called ‘sustainable development’. It points to a ‘dynamical structure’, which is capable of ‘adapting to an ever changing environment’. Life on the planet earth is only possible from the very beginning on account of this fundamental capability starting with the first cells and being kept strongly alive through all the 3.5 Billion years (10^9) in all the following fascinating developments.

This capability to be able to ‘adapt to an ever changing environment’ implies the ability to change the ‘working structure, the body’ in a way, that the structure can change to respond in new ways, if the environment changes. Such a change has two sides: (i) the real ‘production’ of the working structures of a living system, and (ii) the ‘knowledge’, which is necessary to ‘inform’ the processes of formation and keeping an organism ‘in action’. And these basic mechanisms have additionally (iii) to be ‘distributed in a whole population’, whose sheer number gives enough redundancy to compensate for ‘wrong proposals’.

Knowing this the appearance of the homo sapiens life form manifests a qualitative shift in the structure of the adaption so far: surely prepared by several Millions of years the body of the homo sapiens with an unusual brain enabled new forms of ‘understanding the world’ in close connection with new forms of ‘communication’ and ‘cooperation’. With the homo sapiens the brains became capable to talk — mediated by their body and the surrounding body world — with other brains hidden in other bodies in a way, which enabled the sharing of ‘meaning’ rooted in the body world as well in the own body. This capability created by communication a ‘network of distributed knowledge’ encoded in the shared meaning of individual meaning functions. As long as communication with a certain meaning function with the shared meanings ‘works’, as long does this distributed knowledge’ exist. If the shared meaning weakens or breaks down this distributed knowledge is ‘gone’.

Thus, a homo sapiens population has not to wait for another generation until new varieties of their body structures could show up and compete with the changing environment. A homo sapiens population has the capability to perceive the environment — and itself — in a way, that allows additionally new forms of ‘transformations of the perceptions’ in a way, that ‘cognitive varieties of perceived environments’ can be ‘internally produced’ and being ‘communicated’ and being used for ‘sequences of coordinated actions’ which can change the environment and the homo sapiens them self.

The cultural history then shows — as Lévy has outlined shortly on his pages 5-10 — that the homo sapiens population (distributed in many competing smaller sub-populations) ‘invented’ more and more ‘behavior pattern’, ‘social rules’ and a rich ‘diversity of tools’ to improve communication and to improve the representation and processing of knowledge, which in turn helped for even more complex ‘sequences of coordinated actions’.

Sustainability & Collective Intelligence

Although until today there are no commonly accepted definitions of ‘intelligence’ and of ‘knowledge’ available [6], it makes some sense to locate ‘knowledge’ and ‘intelligence’ in this ‘communication based space of mutual coordinated actions’. And this embedding implies to think about knowledge and intelligence as a property of a population, which ‘collectively’ is learning, is understanding, is planning, is modifying its environment as well as them self.

And having this distributed capability a population has all the basics to enable a ‘sustainable development’.

Therefore the capability for a sustainable development is an emergent capability based on the processes enabled by a distributed knowledge enabled by a collective intelligence.

Having sketched out this then all the wonderful statements of Lévy seem to be ‘true’ in that they describe a dynamic reality which is provided by biological life as such.

A truly Open Space with Real Boundaries

Looking from the outside onto this biological mystery of sustainable processes based on collective intelligence using distributed knowledge one can identify incredible spaces of possible continuations. In principle these spaces are ‘open spaces’.

Looking to the details of this machinery — because we are ‘part of it’ — we know by historical and everyday experience that these processes can fail every minute, even every second.

To ‘improve’ a given situation one needs (i) not only a criterion which enables a judgment about something to be classified as being ‘not good’ (e.g. the given situation), one needs further (ii) some ‘minimal vision’ of a ‘different situation’, which can be classified by a criterion as being ‘better’. And, finally, one needs (iii) a minimal ‘knowledge’ about possible ‘actions’ which can change the given situation in successive steps to transform it into the envisioned ‘new better situation’ functioning as a ‘goal’.

Looking around, looking back, everybody has surely experiences from everyday life that these three tasks are far from being trivial. To judge something to be ‘not good’ or ‘not good enough’ presupposes a minimum of ‘knowledge’ which should be sufficiently evenly be ‘distributed’ in the ‘brains of all participants’. Without a sufficient agreement no common judgment will be possible. At the time of this writing it seems that there is plenty of knowledge around, but it is not working as a coherent knowledge space accepted by all participants. Knowledge battles against knowledge. The same is effective for the tasks (ii) and (iii).

There are many reasons why it is no working. While especially the ‘big challenges’ are of ‘global nature’ and are following a certain time schedule there is not too much time available to ‘synchronize’ the necessary knowledge between all. Mankind has until now supportet predominantly the sheer amount of knowledge and ‘individual specialized solutions’, but did miss the challenge to develop at the same time new and better ‘common processes’ of ‘shared knowledge’. The invention of computer, networks of computer, and then the multi-faceted cyberspace is a great and important invention, but is not really helpful as long as the cyberspace has not become a ‘genuin human-like’ tool for ‘distributed human knowledge’ and ‘distributed collective human-machine intelligence’.

Truth

One of the most important challenges for all kinds of knowledge is the ability to enable a ‘knowledge inspired view’ of the environment — including the actor — which is ‘in agreement with the reality of the environment’; otherwise the actions will not be able to support life in the long run. [7] Such an ‘agreement’ is a challenge, especially if the ‘real processes’ are ‘complex’ , ‘distributed’ and are happening in ‘large time frames’. As all human societies today demonstrate, this fundamental ability to use ’empirically valid knowledge’ is partially well developed, but in many other cases it seems to be nearly not in existence. There is a strong — inborn ! — tendency of human persons to think that the ‘pictures in their heads’ represent ‘automatically’ such a knowledge what is in agreement with the real world. It isn’t. Thus ‘dreams’ are ruling the everyday world of societies. And the proportion of brains with such ‘dreams’ seems to grow. In a certain sense this is a kind of ‘illness’: invisible, but strongly effective and highly infectious. Science alone seems to be not a sufficient remedy, but it is a substantial condition for a remedy.

COMMENTS

[*] The decisive hint for this book came from Athene Sorokowsky, who is member of my research group.

[1] Gerd Doeben-Henisch,The general idea of the oksimo paradigm: https://www.uffmm.org/2022/01/24/newsletter/, January 2022

[2] Pierre Lévy in wkp-en: https://en.wikipedia.org/wiki/Pierre_L%C3%A9vy

[3] Karl Popper in wkp-en: https://en.wikipedia.org/wiki/Karl_Popper. One of the papers I have written commenting on Popper can be found HERE.

[4] Pierre Lévy, intlekt – metadata, see: https://intlekt.io/blog/

[5] Who wants to know, what Lévy ‘really’ has written has to go back to the text of Lévy directly. … then the reader will read the text of Lévy with ‘his own point of view’ … indeed, even then the reader will not know with certainty, whether he did really understand Lévy ‘right’. … reading a text is always a ‘dialogue’ .. .

[6] Not in Philosophie, not in the so-called ‘Humanities’, not in the Social Sciences, not in the Empirical Sciences, and not in Computer Science!

[7] The ‘long run’ can be very short if you misjudge in the traffic a situation, or a medical doctor makes a mistake or a nuclear reactor has the wrong sensors or ….

Continuation

See HERE.

NEWSLETTER

eJournal: uffmm.org
ISSN 2567-6458, 24. January 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This post is part of the uffmm science blog.

INTENTION

This is the place for short summaries of topics about which  the author is writing in his German blogs (cognitiveagent.org (Philosophy, Science ), oksimo.org (a new paradigm how people can together turn everything in a simulation by only using their everyday language))

NEWSLETTER January 24, 2022

Software-Paradigm

Since the beginning of the development of the oksimo software I was urged to distinguish between the oksimo software and the oksimo paradigm. The oksimo software is some software which appears to the user as an interface by a web browser, able to do some work, and the oksimo paradigm stands for the whole ‘action space’ which is possible for   human actors using the oksimo software. We know from daily practice that the  ‘software’ — until now in use — is important and big; the software is somehow the ‘store of knowledge’ coded in some language. In the context of the oksimo paradigm the software is ‘small’ and ‘unimportant’. The only contribution of the software is to support human actors to talk about the world in their everyday language in a way, that these talks will automatically be turned into simulations as well as full fledged theories. That’s it. The computer as such does not understand anything. This is a new kind of ‘collective man:machine intelligence’.

Concrete Simulations

Because the main experience while communicating the ideas of this new software paradigm is, that people do not understanding this new paradigm — especially the computer science guys have problems, locked by their ‘usual understanding’ of computers — we stopped ‘advertising’ and focus on first practical examples. This year we spent time to set up a real simulation of a  real county in Germany named ‘Main-Kinzig-Kreis (MKK)’ (Perhaps the same will be done in South-Africa with  the Gauteng Province and there mostly from the Tshwane District.)

Clearly these models will to the end of the year 2022 only cover some main aspects of the county including the related towns and cities, but it will be a real model and can be further developed in the upcoming years.

Because these models are completely WWW-conform and reachable by the ‘ordinary World Wide Web’, everybody can read the results, can try the simulation mode on its own, and can add his own version as an HTML-page.  One can also unify different models  by ‘only pressing a button’. The main intention is, that distributed people can work together as ‘a group’ to share their ideas, visions, experiences.

Software Roadmap

Although we had in the beginning a kind of a Roadmap, what we wanted to have  finished at some time, things went differently: because this whole paradigm is radically new we had in the beginning a basic idea, but not a complete understanding of everything. And thus it happened that we step wise    learned better what it really is. It became more ‘simpler’ and at the same time ‘more powerful’. From a theoretical point of view it looks now as if it can do nearly everything which humans want from a ‘software for a sustainable future’.

A nice point just now was the understanding how we can use radically everyday language and at the same time all of mathematics. If one understands what mathematics is, how it works in our thinking, than it became very simple.

Meta-Thinking

This whole oksimo (reloaded) software project became only possible because there was during many years a truly multi-disciplinary thinking alive relating different disciplines in a truly trans-disciplinary (= meta-theoretical = philosophical) fashion. What we observe today is a steady growth of always more ‘special disciplines’ but a pondering lack of ‘integration’, of meta-thinking. Nowhere we have really working trans-disciplinary programs, there exist not even ideas/ concepts, how to do it.

Sustainability

The united nations series of conferences starting in 1992 until 2015 brought to the front that the course of life on the planet earth is facing more and more a crisis, because the human race has meanwhile occupied 3/4 of the usable areas of the planet and has changed the whole bio-systems and many important resources. The climate change as such is not a problem, but because the human population — and a working biosphere — is highly sensitive to climate change, it is a growing experience of humans that the conditions of the planet are becoming ‘pressing’. Because these problems are working on a global scale they cannot be solve by single nations alone. The time of ‘nations’ seems to be ‘out’. Either we are ‘one mankind’ or we will lose.

To understand ‘sustainability’ one has to look to the biological evolution with the eyes of many disciplines. Besides biology (with many additional disciplines) it seems to me that   ecology is highly important, theoretical ecology!

As part of the biosphere we humans as biological systems have introduced culture,  technology and society  in the game of life. As part of technology we have also introduced machines called ‘computer’ embedded in networks of ‘everything’. All this can be very valuable tools to master the different kinds of future including the whole biosphere. But this can only happen if the human race learns a bit more what it means to live in a truly sustainable fashion. This begins in the kind of ‘thinking and sharing ideas’. We are — it seems to me — far from such a ‘sustainable thinking’.  The minds are very ‘closed boxes’.

Spirituality

In this uffmm blog I did never write about spirituality, also not in the oksimo.org blog, but I have written several posts in may philosophy blog (about 20 – 30, or even more), and elsewhere.

Most people associate the wording ‘spirituality’ with strange, esoteric things, with religions. This reflects the course of history where different kinds of religions and partially strange movements used this term as ‘their’ term.  But this must not be so, not necessarily.

Spirituality is a genuine property of all biological life which in turn is an ‘outcome’ of the whole universe.  The ‘spiritual’ is not owned by special persons, it belongs to every human person  as a part of it. If one understands ‘life’ in it’s full reality, it is ‘the’ most important event in the whole universe. To understand this one must use everything we know today by the empirical sciences, but clearly more, because the empirical sciences are still lacking a true meta-science. The ‘old philosophy’ has not ‘grown’ ‘with’ the sciences; both are still ‘highly separated’ ….

 

 

OKSIMO MEETS POPPER. The Generalized Oksimo Theory Paradigm

eJournal: uffmm.org
ISSN 2567-6458, 5.April – 5.April  2021
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Last changes: Small corrections, April 8, 2021

CONTEXT

This text is part of a philosophy of science  analysis of the case of the oksimo software (oksimo.com). A specification of the oksimo software from an engineering point of view can be found in four consecutive  posts dedicated to the HMI-Analysis for  this software.

THE GENERALIZED OKSIMO THEORY PARADIGM

The Generalized Oksimo Paradigm
Figure: Overview of the Generalized Oksimo Paradigm

In the preceding sections it has been shown that the oksimo paradigm is principally fitting in the theory paradigm as it has been  discussed by Popper. This is possible because some of the concepts used by Popper have been re-interpreted by re-analyzing the functioning of the symbolic dimension. All the requirements of Popper could be shown to work but now even in a more extended way.

SUSTAINABLE FUTURE

To describe the oksimo paradigm it is not necessary to mention as a wider context the general perspective of sustainability as described by the United Nations [UN][1]. But if one understands the oksiomo paradigm deeper and one knows that from the 17 sustainable development goals [SDGs] the fourth goal [SDG4] is understood by the UN as the central key for the development of all the other SDGs [2], then one can understand this as an invitation to think about that kind of knowledge which could be the ‘kernel technology’ for sustainability. A ‘technology’ is not simply ‘knowledge’, it is a process which enables the participants — here assumed as human actors with built-in meaning functions — to share their experience of the world and as well their hopes, their wishes, their dreams to become true in a reachable future. To be ‘sustainable’ these visions have to be realized in a fashion which keeps the whole of biological life alive on earth as well in the whole universe. Biological life is the highest known value with which the universe is gifted.

Knowledge as a kernel technology for a sustainable future of the whole biological life has to be a process where all human biological life-forms headed by the human actors have to contribute with their experience and capabilities to find those possible future states (visions, goals, …) which can really enable a sustainable future.

THE SYMBOLIC DIMENSION

To enable different isolated brains in different bodies to ‘cooperate’ and thereby to ‘coordinate’ their experience, and their behavior, the only and most effective way to do this is known as ‘symbolic communication’: using expressions of some ordinary language whose ‘meaning’ has been learned by every member of the population beginning with being born on this planet.  Human actors (classified as the life-form ‘homo sapiens’) have the most known elaborated language capability by being able to associate all kinds of experience with expressions of an ordinary language. These ‘mappings’ between expressions and the general experience is taking place ‘inside the brain’ and these mappings are highly ‘adaptive’; they can change over time and they are mostly ‘synchronized’ with the mappings taking place in other brains. Such a mapping is here called a ‘meaning function’ [μ].

DIFFERENT KINDS OF EXPRESSIONS

The different sientific disciplines today have developed many different views and models how to describe the symbolic dimension, their ‘parts’, their functioning. Here we assume only three different kinds of expressions which can be analayzed further with nearly infinite many details.

True Concrete Expressions [S_A]

The ‘everyday case’ occurs if human actors share a real actual situation and they use their symbolic expressions to ‘talk about’ the shared situation, telling each other what is given according to their understanding using their built-in meaning function μ. With regard to the shared knowledge and language these human actors can decide, wether an expression E used in the description is matching the observed situation or not. If the expression is matching than such an expression is classified as being a ‘true expression’. Otherwise it is either undefined or eventually ‘false’ if it ‘contradicts’ directly. Thus the set of all expressions assumed to be true in a actual given situation S is named  here S_A. Let us look to an example: Peter says, “it is raining”, and Jenny says “it is not raining”. If all would agree, that   it is raining, then Peters expression is classified as ‘true’ and Jennys expression as ‘false’. If  different views would exist in the group, then it is not clear what is true or false or undefined in this group! This problem belongs to the pragmatic dimension of communication, where human actors have to find a way to clarify their views of the world. The right view of the situation  depends from the different individual views located in the individual brains and these views can be wrong. There exists no automatic procedure to get a ‘true’ vision of the real world.

General Assumptions [S_U]

It is typical for human actors that they are collecting knowledge about the world including general assumptions like “Birds can fly”, “Ice is melting in the sun”, “In certain cases the covid19-virus can bring people to death”, etc. These expressions are usually understood as ‘general’ rules  because they do not describe a concrete single case but are speaking of many possible cases. Such a general rule can be used within some logical deduction as demonstrated by the  classical greek logic:  ‘IF it is true that  “Birds can fly” AND we have a certain fact  “R2D2 is a bird” THEN we can deduce the fact  “R2D2 can fly”‘.  The expression “R2D2 can fly”  claims to be  true. Whether this is ‘really’ the case has to be shown in a real situation, either actually or at some point in the future. The set of all assumed general assumptions is named here S_U.

Possible Future States [S_V]

By experience and some ‘creative’ thinking human actors can imagine concrete situations, which are not yet actually given but which are assumed to be ‘possible’; the possibility can be interpreted as some ‘future’ situation. If a real situation would be reached which includes the envisioned state then one could say that the vision has become  ‘true’. Otherwise the envisioned state is ‘undefined’: perhaps it can become true or not.  In human culture there exist many visions since hundreds or even thousands of years where still people are ‘believing’ that they will become ‘true’ some day. The set of all expressions related to a vision is named here S_V.

REALIZING FUTURE [X, X]

If the set of expressions S_V  related to a ‘vision’ (accompanied by many emotions, desires, details of all kinds) is not empty,  then it is possible to look for those ‘actions’ which with highest ‘probability’ π can ‘change’ a given situation S_A in a way that the new situation S’  is becoming more and more similar to the envisioned situation S_V. Thus a given goal (=vision) can inspire a ‘construction process’ which is typical for all kinds of engineering and creative thinking. The general format of an expression to describe a change is within the oksimo paradigm assumed as follows:

  1. With regard to a given situation S
  2. Check whether a certain set of expressions COND is a subset of the expressions of S
  3. If this is the case then with probability π:
  4. Remove all expressions of the set Eminus from S,
  5. Add all expressions of the set Eplus to S
  6. and update (compute) all parameters of the set Model

In a short format:

S’π = S – Eminus + Eplus & MODEL(S)

All change rules together represent the set X. In the general theory paradigm the change rules X represent the inference rules, which together with a general ‘inference concept’ X constitute the ‘logic’ of the theory. This enables the following general logical relation:

{S_U, S_A} <S_A, S1, S2, …, Sn>

with the continuous evaluation: |S_V ⊆ Si| > θ. During the whole construction it is possible to evaluate each individual state whether the expressions of the vision state S_V are part of the actual state Si and to which degree.

Such a logical deduction concept is called a ‘simulation’ by using a ‘simulator’ to repeat the individual deductions.

POSSIBLE EXTENSIONS

The above outlined oksimo theory paradigm can easily be extended by some more features:

  1. AUTONOMOUS ACTORS: The change rules X so far are ‘static’ rules. But we know from everyday life that there are many dynamic sources around which can cause some change, especially biological and non-biological actors. Every such actors can be understood as an input-output system with an adaptive ‘behavior function’ φ.  Such a behavior can not be modeled by ‘static’ rules alone. Therefore one can either define theoretical models of such ‘autonomous’ actors with  their behavior and enlarge the set of change rules X with ‘autonomous change rules’ Xa as Xa ⊆ X. The other variant is to include in real time ‘living autonomous’ actors as ‘players’ having the role of an ‘autonomous’ rule and being enabled to act according to their ‘will’.
  2. MACHINE INTELLIGENCE: To run a simulation will always give only ‘one path’ P in the space of possible states. Usually there would be many more paths which can lead to a goal state S_V and the accompanying parameters from Model can be different: more or less energy consumption, more or less financial losses, more or less time needed, etc. To improve the knowledge about the ‘good candidates’ in the possible state space one can introduce  general machine intelligence algorithms to evaluate the state space and make proposals.
  3. REAL-TIME PARAMETERS: The parameters of Model can be connected online with real measurements in near real-time. This would allow to use the collected knowledge to ‘monitor’ real processes in the world and based on the collected knowledge recommend actions to react to some states.
COMMENTS

[1] The 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for people and the planet, now and into the future. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries – developed and developing – in a global partnership. They recognize that ending poverty and other deprivations must go hand-in-hand with strategies that improve health and education, reduce inequality, and spur economic growth – all while tackling climate change and working to preserve our oceans and forests. See PDF: https://sdgs.un.org/sites/default/files/publication/21252030%20Agenda%20for%20Sustainable%20Development%20web.pdf

[2] UN, SDG4, PDF, Argumentation why the SDG4 ist fundamental for all other SDGs: https://sdgs.un.org/sites/default/files/publications/2275sdbeginswitheducation.pdf

 

 

OKSIMO MEETS POPPER. The Oksimo Theory Paradigm

eJournal: uffmm.org
ISSN 2567-6458, 2.April – 2.April  2021
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of a philosophy of science  analysis of the case of the oksimo software (oksimo.com). A specification of the oksimo software from an engineering point of view can be found in four consecutive  posts dedicated to the HMI-Analysis for  this software.

THE OKSIMO THORY PARADIGM

The Oksimo Theory Paradigm
Figure 1: The Oksimo Theory Paradigm

The following text is a short illustration how the general theory concept as extracted from the text of Popper can be applied to the oksimo simulation software concept.

The starting point is the meta-theoetical schema as follows:

MT=<S, A[μ], E, L, AX, ⊢, ET, E+, E-, true, false, contradiction, inconsistent>

In the oksimo case we have also a given empirical context S, a non-epty set of human actors A[μ] whith a built-in meaning function for the expressions E of some language L, some axioms AX as a subset of the expressions E, an inference concept , and all the other concepts.

The human actors A[μ] can write  some documents with the expressions E of language L. In one document S_U they can write down some universal facts they belief that these are true (e.g. ‘Birds can fly’).  In another document S_E they can write down some empirical facts from the given situation S like ‘There is something named James. James is a bird’. And somehow they wish that James should be able to fly, thus they write down a vision text S_V with ‘James can fly’.

The interesting question is whether it is possible to generate a situation S_E.i in the future, which includes the fact ‘James can fly’.

With the knowledge already given they can built the change rule: IF it is valid, that {Birds can fly. James is a bird} THEN with probability π = 1 add the expression Eplus = {‘James can fly’} to the actual situation S_E.i. EMinus = {}. This rule is then an element of the set of change rules X.

The simulator X works according to the schema S’ = S – Eminus + Eplus.

Because we have S=S_U + S_E we are getting

S’ = {Birds can fly. Something is named James. James is a bird.} – Eminus + Eplus

S’ = {Birds can fly. Something is named James. James is a bird.} – {}+ {James can fly}

S’ = {Birds can fly. Something is named James. James is a bird. James can fly}

With regard to the vision which is used for evaluation one can state additionally:

|{James can fly} ⊆ {Birds can fly. Something is named James. James is a bird. James can fly}|= 1 ≥ 1

Thus the goal has been reached with 1 meaning with 100%.

THE ROLE OF MEANING

What makes a certain difference between classical concepts of an empirical theory and the oksimo paradigm is the role of meaning in the oksimo paradigm. While the classical empirical theory concept is using formal (mathematical) languages for their descriptions with the associated — nearly unsolvable — problem how to relate these concepts to the intended empirical world, does the oksimo paradigm assume the opposite: the starting point is always the ordinary language as basic language which on demand can be extended by special expressions (like e.g. set theoretical expressions, numbers etc.).

Furthermore it is in the oksimo paradigm assumed that the human actors with their built-in meaning function nearly always are able to  decided whether an expression e of the used expressions E of the ordinary language L is matching certain properties of the given situation S. Thus the human actors are those who have the authority to decided by their meaning whether some expression is actually true or not.

The same holds with possible goals (visions) and possible inference rules (= change rules). Whether some consequence Y shall happen if some condition X is satisfied by a given actual situation S can only be decided by the human actors. There is no other knowledge available then that what is in the head of the human actors. [1] This knowledge can be narrow, it can even be wrong, but human actors can only decide with that knowledge what is available to them.

If they are using change rules (= inference rules) based on their knowledge and they derive some follow up situation as a theorem, then it can happen, that there exists no empiricial situation S which is matching the theorem. This would be an undefined truth case. If the theorem t would be a contradiction to the given situation S then it would be clear that the theory is inconsistent and therefore something seems to be wrong. Another case cpuld be that the theorem t is matching a situation. This would confirm the belief on the theory.

COMMENTS

[1] Well known knowledge tools are since long libraries and since not so long data-bases. The expressions stored there can only be of use (i) if a human actor knows about these and (ii) knows how to use them. As the amount of stored expressions is increasing the portion of expressions to be cognitively processed by human actors is decreasing. This decrease in the usable portion can be used for a measure of negative complexity which indicates a growng deterioration of the human knowledge space.  The idea that certain kinds of algorithms can analyze these growing amounts of expressions instead of the human actor themself is only constructive if the human actor can use the results of these computations within his knowledge space.  By general reasons this possibility is very small and with increasing negativ complexity it is declining.

 

 

 

HMI ANALYSIS, Part 4: Tool based Actor Story Development with Testing and Gaming

Integrating Engineering and the Human Factor (info@uffmm.org)
eJournal uffmm.org ISSN 2567-6458, March 3-4, 2021,
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Last change: March 4, 2021, 07:49h (Minor corrections; relating to the UN SDGs)

HISTORY

As described in the uffmm eJournal  the wider context of this software project is an integrated  engineering theory called Distributed Actor-Actor Interaction [DAAI] further extended to the Collective Man-Machine Intelligence [CM:MI] paradigm.  This document is part of the Case Studies section.

HMI ANALYSIS, Part 4: Tool based Actor Story Development with Testing and Gaming

Context

This text is preceded by the following texts:

INFO GRAPH

Overview about different scenarios which will be possible for the development, simulation, testing and gaming of actor stories using the oksimo software tool

Introduction

In the preceding post it has been explained, how one can format an actor story [AS] as a theory in the  format  of  an Evaluated Theory Tε with Algorithmic Intelligence:   Tε,α=<M,∑,ε,α>.

In the following text it will be explained which kinds of different scenarios will be possible to elaborate, to simulate, to test, and to enable gaming with  an actor story theory by using the oksimo software tool.

UNIVERSAL TEAM

The classical distinctions between certain types of managers, special experts and the rest of the world is given up here in favor of a stronger generalization: everybody is a potential expert with regard to a future, which nobody knows. This is emphasized by the fact, that everybody can use its usual mother tongue, a normal language, every language. Nothing more is needed.

BASIC MODELS (S, X)

As minimal elements for all possible applications it is assumed here that the experts define at least a given situation (state) [S] and a set of change rules [X].

The given state S is  either (i)  taken as it is or (ii)  as a state which  should be improved. In both cases the initial state S is called the start state [S0].

The change rules X describe possible changes which transform a given state S into a changed successor state S’.

A pair of S and X as (S,X) is called a basic model M(S,X). One can define as many models as one wants.

A DIRECTION BY A VISION V

A vision [V] can describe a possible state SV  in an assumed future. If such a state SV is given, then this state becomes a goal state SGoal In this case  we assume V ≠ 0. If no explicit goal is given, then we assume V = 0.

DEVELOPMENT BY GOALS

If a vision is given (V ≠ 0), then the vision can be used to induce a direction which can/ shall be approached by creating a set X, which enables the generation of a sequence of states with the start state S0 as first state followed by successor state Si until the goal state SGoal has been reached or at least it holds that the goal state is a subset of the reached state: SGoalSn.

It is possible to use many basic models M(S,X) in parallel and for each model Mi one can define a different goal Vi (the typical situation in a pluralistic society).

Thus there can be many basic theories T(M,V) in parallel.

STEADY STATES (V = 0)

If no explicit visions are defined (V = 0) then every direction of change is allowed. A basic steady state theory T(M,V) with V = 0 can   be written as T(M,0). Whether such a case can be of interest is not clear at the moment.

BASIC INTERACTION PATTERNS

The following interaction modes are assumed as typical cases:

  1. N-1: Within an online session an interactive webpage with the oksimo software is active and the whole group can interact with the oksimo software tool.
  2. N-N-1: N-many participants can individually login into the interactive oksimo website and being logged in they can collaborate within the oksimo software with one project.
  3. N-N-N: N-many participants can individually login into the interactive oksimo website and there everybody can run its own process or can collaborate in various ways.

The default case is case (1). The exact dates for the availability of modes (2) – (3) depends from how fast the roadmap can be realized.

BASIC APPLICATIONS
  1. Exploring Simulation-Based Development [ESBD] (V ≠ 0): If the main goal is to find a path from a given state today S (Now) to an envisioned state V in the future then one has  to collect appropriate change rules X to approach the final goal state SGoal better and better. Activating the simulator ∑ during search and construction phase at will can be of great help, especially if the documents (S, X, V) are becoming more and more complex.
  2. Embedded Simulation-Based  Testing [ESBT] (V ≠ 0): If a basic  actor story theory T(M,) is given with a given goal (V ≠ 0) then it is of great help if the simulation is done in interactive mode where the simulator is not applying the change rules by itself but by asking different logged in users which rule they want to apply and how. These tests show not only which kinds of errors will occur but they can also show during n-many repetitions to which degree an user  can learn to behave task-conform. If the tests will not show the expected outcomes then this can point  to possible deficiencies of the software as well to specialties of the user.
  3. Embedded Simulation-Based Gaming [ESBTG] (V ≠ 0):  The case of gaming is partially  different to the case of testing.  Although it is assumed here too that at least one vision (goal) is given, it is additionally assumed that  there exists  a competition between different players or different teams. Different to testing exists in gaming according to the goal(s) the role of a winner: that player/ team which has reached a defined  goal state before the other player/ teams,  has won. As a side-effect of gaming one can also evaluate the playing environment and give some feedback to the developers.
ALGORITHMIC INTELLIGENCE
  1. Case ESBD, T(S,X,V,∑,ε,α): Because a normal simulation with the simulator always does  produce only one path from the start state to the goal state it is desirable to have an algorithm α which would run on demand as many times as wanted and thereby the algorithm α would search for all possible paths and at the same time it would look for those derivations, where the goal state satisfies with  ε certain special requirements. Thus the result from the application of α onto a given model M with the vision V would generate the set SV* of all those final states which satisfy the special requirements.
  2. Case ESBG, T(S,X,V,∑,ε,α):   The case of gaming allows at least three kinds of interesting applications for algorithmic intelligence: (i) Introduce non-biological players with learning capabilities which can act simultaneously with the biological players; (ii) Introduce non-biological players with learning capabilities which have to learn how to support, to assist, to train biological player. This second case addresses the challenging task to develop algorithmic tutors for several kinds of learning tasks. (iii) Another variant of case (ii) is to enable the development of a personal algorithmic assistant who works only with one person on a long-term basis.

The kinds of algorithmic Intelligence in (2)(i)-(iii) are different to the  mentioned algorithmic intelligence α in (1).

TYPES OF ACTORS

As the default standard case of an actor it is assumed that there are biological actors, usually human persons, which will not be analyzed with their inner structure [IS]. While the behavior of every system — and  therefore any biological system too — can be described with a behavior function φ: I x IS —> IS x O (if one has all the necessary knowledge), in the default case of biological systems  no behavior function φ is specified, φ = 0. During interactive simulations biological systems act by themselves.

If non-biological actors are used — e.g. automata with a certain machine program (an algorithm) — then one can use these only if one has a fully specified behavior function φ. From this follows that a  change rule which is associated with a non-biological actor has in its Eplus and in its Eminus part not a concrete expression but a variable, which will be computed during the simulation by the non-biological actor depending from its input and its behavior function φ: φ(input)IS=(Eplus, Eminus)IS.

FINAL COMMENT

Everybody who has read the parts (1) – (4) has now a general knowledge about the motivation to develop the oksimo software tool to support human kind to have a better communication and thinking of possible futures and a first understanding (hopefully :-)) how this tool can work. Reading the UN sustainable development goals [SDGs] [1] you will learn, that the SDG4 (Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all) is fundamental to all other SDGs. The oksimo software tool is one tool to be of help to reach these goals.

REFERENCES

[1] The 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for people and the planet, now and into the future. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries – developed and developing – in a global partnership. They recognize that ending poverty and other deprivations must go hand-in-hand with strategies that improve health and education, reduce inequality, and spur economic growth – all while tackling climate change and working to preserve our oceans and forests. See PDF: https://sdgs.un.org/sites/default/files/publication/21252030%20Agenda%20for%20Sustainable%20Development%20web.pdf

[2] UN, SDG4, PDF, Argumentation why the SDG4 ist fundamental for all other SDGs: https://sdgs.un.org/sites/default/files/publications/2275sdbeginswitheducation.pdf

 

 

 

 

 

 

 

 

HMI Analysis for the CM:MI paradigm. Part 2. Problem and Vision

Integrating Engineering and the Human Factor (info@uffmm.org)
eJournal uffmm.org ISSN 2567-6458, February 27-March 16, 2021,
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Last change: March 16, 2021 (minor corrections)

HISTORY

As described in the uffmm eJournal  the wider context of this software project is an integrated  engineering theory called Distributed Actor-Actor Interaction [DAAI] further extended to the Collective Man-Machine Intelligence [CM:MI] paradigm.  This document is part of the Case Studies section.

HMI ANALYSIS, Part 2: Problem & Vision

Context

This text is preceded by the following texts:

Introduction

Before one starts the HMI analysis  some stakeholder  — in our case are the users stakeholder as well as  users in one role —  have to present some given situation — classifiable as a ‘problem’ — to depart from and a vision as the envisioned goal to be realized.

Here we give a short description of the problem for the CM:MI paradigm and the vision, what should be gained.

Problem: Mankind on the Planet Earth

In this project  the mankind  on the planet earth is  understood as the primary problem. ‘Mankind’ is seen here  as the  life form called homo sapiens. Based on the findings of biological evolution one can state that the homo sapiens has — besides many other wonderful capabilities — at least two extraordinary capabilities:

Outside to Inside

The whole body with the brain is  able to convert continuously body-external  events into internal, neural events. And  the brain inside the body receives many events inside the body as external events too. Thus in the brain we can observe a mixup of body-external (outside 1) and body-internal events (outside 2), realized as set of billions of neural processes, highly interrelated.  Most of these neural processes are unconscious, a small part is conscious. Nevertheless  these unconscious and conscious events are  neurally interrelated. This overall conversion from outside 1 and outside 2 into neural processes  can be seen as a mapping. As we know today from biology, psychology and brain sciences this mapping is not a 1-1 mapping. The brain does all the time a kind of filtering — mostly unconscious — sorting out only those events which are judged by the brain to be important. Furthermore the brain is time-slicing all its sensory inputs, storing these time-slices (called ‘memories’), whereby these time-slices again are no 1-1 copies. The storing of time-sclices is a complex (unconscious) process with many kinds of operations like structuring, associating, abstracting, evaluating, and more. From this one can deduce that the content of an individual brain and the surrounding reality of the own body as well as the world outside the own body can be highly different. All kinds of perceived and stored neural events which can be or can become conscious are  here called conscious cognitive substrates or cognitive objects.

Inside to Outside (to Inside)

Generally it is known that the homo sapiens can produce with its body events which have some impact on the world outside the body.  One kind of such events is the production of all kinds of movements, including gestures, running, grasping with hands, painting, writing as well as sounds by his voice. What is of special interest here are forms of communications between different humans, and even more specially those communications enabled by the spoken sounds of a language as well as the written signs of a language. Spoken sounds as well as written signs are here called expressions associated with a known language. Expressions as such have no meaning (A non-speaker of a language L can hear or see expressions of the language L but he/she/x  never will understand anything). But as everyday experience shows nearly every child  starts very soon to learn which kinds of expressions belong to a language and with what kinds of shared experiences they can be associated. This learning is related to many complex neural processes which map expressions internally onto — conscious and unconscious — cognitive objects (including expressions!). This mapping builds up an internal  meaning function from expressions into cognitive objects and vice versa. Because expressions have a dual face (being internal neural structures as well as being body-outside events by conversions from the inside to body-outside) it is possible that a homo sapiens  can transmit its internal encoding of cognitive objects into expressions from his  inside to the outside and thereby another homo sapiens can perceive the produced outside expression and  can map this outside expression into an intern expression. As far as the meaning function of of the receiving homo sapiens  is sufficiently similar to the meaning function of  the sending homo sapiens there exists some probability that the receiving homo sapiens can activate from its memory cognitive objects which have some similarity with those of  the sending  homo sapiens.

Although we know today of different kinds of animals having some form of language, there is no species known which is with regard to language comparable to  the homo sapiens. This explains to a large extend why the homo sapiens population was able to cooperate in a way, which not only can include many persons but also can stretch through long periods of time and  can include highly complex cognitive objects and associated behavior.

Negative Complexity

In 2006 I introduced the term negative complexity in my writings to describe the fact that in the world surrounding an individual person there is an amount of language-encoded meaning available which is beyond the capacity of an  individual brain to be processed. Thus whatever kind of experience or knowledge is accumulated in libraries and data bases, if the negative complexity is higher and higher than this knowledge can no longer help individual persons, whole groups, whole populations in a constructive usage of all this. What happens is that the intended well structured ‘sound’ of knowledge is turned into a noisy environment which crashes all kinds of intended structures into nothing or badly deformed somethings.

Entangled Humans

From Quantum Mechanics we know the idea of entangled states. But we must not dig into quantum mechanics to find other phenomena which manifest entangled states. Look around in your everyday world. There exist many occasions where a human person is acting in a situation, but the bodily separateness is a fake. While sitting before a laptop in a room the person is communicating within an online session with other persons. And depending from the  social role and the  membership in some social institution and being part of some project this person will talk, perceive, feel, decide etc. with regard to the known rules of these social environments which are  represented as cognitive objects in its brain. Thus by knowledge, by cognition, the individual person is in its situation completely entangled with other persons which know from these roles and rules  and following thereby  in their behavior these rules too. Sitting with the body in a certain physical location somewhere on the planet does not matter in this moment. The primary reality is this cognitive space in the brains of the participating persons.

If you continue looking around in your everyday world you will probably detect that the everyday world is full of different kinds of  cognitively induced entangled states of persons. These internalized structures are functioning like protocols, like scripts, like rules in a game, telling everybody what is expected from him/her/x, and to that extend, that people adhere to such internalized protocols, the daily life has some structure, has some stability, enables planning of behavior where cooperation between different persons  is necessary. In a cognitively enabled entangled state the individual person becomes a member of something greater, becoming a super person. Entangled persons can do things which usually are not possible as long you are working as a pure individual person.[1]

Entangled Humans and Negative Complexity

Although entangled human persons can principally enable more complex events, structures,  processes, engineering, cultural work than single persons, human entanglement is still limited by the brain capacities as well as by the limits of normal communication. Increasing the amount of meaning relevant artifacts or increasing the velocity of communication events makes things even more worse. There are objective limits for human processing, which can run into negative complexity.

Future is not Waiting

The term ‘future‘ is cognitively empty: there exists nowhere an object which can  be called ‘future’. What we have is some local actual presence (the Now), which the body is turning into internal representations of some kind (becoming the Past), but something like a future does not exist, nowhere. Our knowledge about the future is radically zero.

Nevertheless, because our bodies are part of a physical world (planet, solar system, …) and our entangled scientific work has identified some regularities of this physical world which can be bused for some predictions what could happen with some probability as assumed states where our clocks are showing a different time stamp. But because there are many processes running in parallel, composed of billions of parameters which can be tuned in many directions, a really good forecast is not simple and depends from so many presuppositions.

Since the appearance of homo sapiens some hundred thousands years ago in Africa the homo sapiens became a game changer which makes all computations nearly impossible. Not in the beginning of the appearance of the homo sapiens, but in the course of time homo sapiens enlarged its number, improved its skills in more and more areas, and meanwhile we know, that homo sapiens indeed has started to crash more and more  the conditions of its own life. And principally thinking points out, that homo sapiens could even crash more than only planet earth. Every exemplar of a homo sapiens has a built-in freedom which allows every time to decide to behave in a different way (although in everyday life we are mostly following some protocols). And this built-in freedom is guided by actual knowledge, by emotions, and by available resources. The same child can become a great musician, a great mathematician, a philosopher, a great political leader, an engineer, … but giving the child no resources, depriving it from important social contexts,  giving it the wrong knowledge, it can not manifest its freedom in full richness. As human population we need the best out of all children.

Because  the processing of the planet, the solar system etc.  is going on, we are in need of good forecasts of possible futures, beyond our classical concepts of sharing knowledge. This is where our vision enters.

VISION: DEVELOPING TOGETHER POSSIBLE FUTURES

To find possible and reliable shapes of possible futures we have to exploit all experiences, all knowledge, all ideas, all kinds of creativity by using maximal diversity. Because present knowledge can be false — as history tells us –, we should not rule out all those ideas, which seem to be too crazy at a first glance. Real innovations are always different to what we are used to at that time. Thus the following text is a first rough outline of the vision:

  1. Find a format
  2. which allows any kinds of people
  3. for any kind of given problem
  4. with at least one vision of a possible improvement
  5. together
  6. to search and to find a path leading from the given problem (Now) to the envisioned improved state (future).
  7. For all needed communication any kind of  everyday language should be enough.
  8. As needed this everyday language should be extendable with special expressions.
  9. These considerations about possible paths into the wanted envisioned future state should continuously be supported  by appropriate automatic simulations of such a path.
  10. These simulations should include automatic evaluations based on the given envisioned state.
  11. As far as possible adaptive algorithms should be available to support the search, finding and identification of the best cases (referenced by the visions)  within human planning.

REFERENCES or COMMENTS

[1] One of the most common entangled state in daily life is the usage of normal language! A normal language L works only because the rules of usage of this language L are shared by all speaker-hearer of this language, and these rules are explicit cognitive structures (not necessarily conscious, mostly unconscious!).

Continuation

Yes, it will happen 🙂 Here.