All posts by Gerd Doeben-Henisch

WHY THE WORLD NEEDS ANTHROPOLOGISTS – Review Part 1

eJournal: uffmm.org, ISSN 2567-6458, 1.December  2020
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

ANTHROPOLOGY AND ENGINEERING

The starting point of view in this blog has been and still is the point of engineering, especially the perspective of man-machine interface [MMI], later as Man-Machine Interaction, then  accompanied by   human-computer interaction [HCI] or human-machine interaction [HMI]. While MMI often is discussed in isolation, not as part of engineering, this blog emphasizes a point of view where MMI is understood as an integrated part of systems engineering. The past years have shown, that this integration makes a great difference in the overall layout as well as in the details of the used methods. This integration widened the scope of MMI to the context of engineering in a way which teared down many artificial boundaries in dealing with the subject of MMI. The analysis part of MMI can take into account not only the intended users and a limited set of tasks required for the usage of a system but it can extend the scope to the different kinds of contexts of the intended users as well as the intended service/product as such: cultural patterns, sustainable perspectives, climate relevance, political implications, and more. This triggers the question, whether there are other established scientific disciplines which are sharing this scope with MMI. Traditionally experimental and cognitive psychology has always played an important role as part of the MMI analysis.  Different special disciplines like physiology or neuro-psychology, linguistics, phonetics etc. have played some role too. More recently culture and society have been brought more into the focus of MMI. What about sociology? What about anthropology? The following text discusses a possible role of anthropology in the light of the recent book Why The World Needs Anthropologists?

INTRODUCTION AND CONCLUSION

This review has the addendum ‘Part 1’ pointing to the fact, that this text does not deal with the whole book first, but only with some parts, the introduction and the conclusion.

An Introduction

The introduction of the book is asking, why does the world needs anthropologists?, and the main pattern of the introduction looks back to the old picture of anthropology, and then seeks to identify, what could/is the new paradigm which should be followed.

The roots of anthropology are located in the colonial activities of the British Empire as well as in the federal activities of the USA, which both had a strong bias to serve the political power more than to evolve a really free science. And an enduring gap between the more theoretical anthropology and an applied one is thematised although there existed always  a strong inter-dependency  between both.

To leave the close connection with primarily  governmental interests and to see the relation  between the theory and the different Applications  more positive than negative anthropology is understood  as challenged to rebrand its appearance in the public and in their own practice.

The most vital forces for such a rebranding seem to be rooted in more engagements in societal problems of public interests and thereby challenging the theory to widen their concept and methods.

Besides the classical methods of anthropology (cultural relativism, ethnography, comparison, and contextual understanding)  anthropology has to show that it can make sense beyond pure data, deciphering ambiguity, complexity, and ambivalence, helping with  diversity, investigating the interface between culture, technology, and environment.

What Is Left Out

After the introduction the main chapters of the book  are left out in this text  until later. The chapters in the book are giving examples to the questions, why the world needs anthropology, what have been the motivations for active anthropologists to become one, how they have applied anthropology, and which five tips they would give for practicing and theorizing.

Conclusion

In the conclusion of the book not the five questions are the guiding principle but ‘five axis that matter greatly’, and these five axis are circumscribed as (i) navigate the ethics of change; (ii) own-it in the sense, that an anthropologist should have a self-esteem for his/ her/ x  profession and can co-create it with others; (iii) expand the skill-set; (iv) collaborate, co-create and study-up; (v) recommend as being advisors and consultants.

The stronger commitment with actual societal problems leads anthropology at the crossroads of many processes which require new views, new methods. To gain new knowledge and to do a new practice is  not always accompanied by  known ethical schemata. Doing this induces  ethical questions which have not been known before in this way.  While a new practice is challenging the old knowledge and induces a pressure for change, new versions of knowing can  trigger new forms of practice as well. Theory and application are a dynamic pair where each part learns from the other.

The long-lasting preference of academic anthropology, thinking predominantly  in the mind-setting of   white-western-man, is  more and more resolved  by extending anthropology from academia to application, from man into the diversity of genders, from western culture into all the other cultures, from single persons to assemblies of diverse gatherings living an ongoing discourse with a growing publicity.

This widening of anthropological subjects and methods calls naturally for more interdisciplinarity, transdisciplinarity, and of a constructive attitude  which looks ahead to  possible futures of processes.

Close to this are expressions like collaboration and co-creation with others. In the theory dimension this is reflected by multiperspectivity and a holistic view. In societal development processes — like urban planning — there are different driving forces acting working top-down or acting working bottom-up.

Recommending solutions based on anthropological thinking ending in a yes or no, can be of help and can be necessary because real world processes can not only wait of final answers (which are often not realistic), they need again and again decisions to proceed now.

REFLECTIONS FOLLOWING THE INTRODUCTION AND THE CONCLUSION

The just referred texts making a fresh impression of a discipline in a dynamic movement.

General Knowledge Architecture

For the point of view of MMI (Man-Machine Interface, later HMI Human-Machine Interaction, in my theory extended to DAAI Distributed Actor-Actor Interaction) embedded in systems engineering with an openness for the whole context of society and culture arises the question whether such a dynamic anthropology can be of help.

To clarify this question let us have a short look to the general architecture of knowledge.

Within the everyday world philosophy can be understood as the most general point of view of knowing  and thinking.  Traditionally logic and mathematics can be understood as part of philosophy although today this has been changed. But there are no real reasons for this departure: logic and mathematics are not empirical sciences and they are not engineering.

Empirical science can be understood as specialized extension of philosophical thinking with identifiable characteristics which allow to  differentiate to some extend different  disciplines.  Traditionally all the different disciplines of empirical science have a more theoretical part and a more applied part. But systematically they depend from each other. A theory is only an empirical one, if there exists a clear relationship to the everyday world, and certain aspects of the everyday world are only theoretical entities (data) if there exists a relationship to an explicit theory which gives a formal explanation.

Asking for a  systematic place for engineering it is often said, that it belongs to the applied dimension of empirical science.  But engineering has realized processes, buildings, machines long before there was a scientific framework for to do this, and engineering uses in its engineering processes lots of knowledge which is not part of science. On the other side, yes, engineering is using scientific knowledge as far as it is usable and it is also giving back many questions to science which are not yet solved sufficiently. Therefore it is sound to locate engineering besides science, but   being  part of philosophy dealing with the practical dimensions of life.

What About Anthropology?

While philosophy (with logic and mathematics) is ‘on top’ of empirical science and engineering, it is an interesting question where to place anthropology?

While empirical science as well as engineering are inheriting all what philosophy provides remains the question whether  anthropology is more an empirical science or more engineering or some kind of a hybrid system with roots in empirical science as well as in engineering?

Looking back into history it could arise the impression that anthropology is more a kind of an empirical science with strong roots in academia, but doing  fieldwork to feed the theories.

Looking to the new book it could support the image that anthropology should be more like engineering: identifying  open problems in society and trying to transform these problems — like engineers — into satisfying solutions, at least on the level of counseling.

Because in our societies the universities have traditionally a higher esteem then the engineers — although the engineers  are all  trained by highly demanding university courses — it could be a bias in the thinking of  anthropologist not to think of their discipline   as engineering.

If one looks to the real world than everything which  makes human societies livable is realized by engineers. Yes, without science many of the today solutions wouldn’t be possible, but no single scientific theory has ever enabled directly some practical stuff.  And without the engineers there would not exist any of the modern machines used for measurements and experiments for science. Thus both are intimately  interrelated: science inspires engineering and engineering inspires and enables science, but both are genuinely different and science and engineering play their own fundamental role.

Thus if I am reading the new book as engineer (attention: I am also a philosopher and I am trained in the Humanities too!) then I think there are more arguments to understand anthropology  as engineering than as a pure empirical science. In the light of my distributed actor-actor interaction paradigm, which is a ‘spinoff’ of engineering and societal thinking it seems very ‘naturally’ to think of anthropology as a kind of social engineering.

Let us discuss both perspectives a bit more, thereby not excluding the hybrid version.

1) Anthropology as Engineering

The basic idea of engineering is to enable a change process which is completely transparent in all respects: Why, Who, Where, When, How etc. The process starts with explicit preferences turning some known reality into a problem on account of some visions which have been imagined and which have become ranked higher than the given known reality. And then the engineers try to organized an appropriate change process which will lead from the given situation to a new situation until some date in the future where the then given situation — the envisioned goal state — has become real and the situation from the beginning, which has been ranked down, has disappeared, or is at least weakened in a way that one can say, yes, it has changed.

Usually engineers are known to enable change processes which enable the production of everyday things (tools, products, machines, houses, plants, ships, airplanes, …), but to the extend that the engineering is touching the everyday life deeper and deeper (e.g. the global digital revolution absorbing more and more from the real life processes by transforming them into digital realities forcing human persons to act digitally and not any more with their bodies in the everyday world) the sharp boundary between engineering products and the societal life of human persons is vanishing. In such a context engineering is becoming social engineering even if the majority of traditional engineers this doesn’t see yet in this way. As the traditional discipline MMI Man-Machine Interface and then  expanded to HMI Human-Machine Interaction and further morphed into DAAI Distributed Actor-Actor Interaction this  already manifests, that the realm of human persons, yes  the whole of society is already included in engineering.  The border between machines and human actors is already at least fuzzy and the mixing of technical devices and human actors (as well as all other biological actors) has already gained a degree which does not allow any longer a separation.

These ideas would argue for the option to see anthropology as social engineering: thematizing all the important visions which seem to be helpful or important for a good future of modern mankind, and to help to organize change processes, which will support approaching this better future. That these visions can fail, can be wrong is part of the ever lasting battle of the homo sapiens to gain the right knowledge.

2) Anthropology as  an Empirical Science

… to be continued …

3) Anthropology as a Hybrid Couple of Science and Engineering

… to be continued …

 

 

KOMEGA REQUIREMENTS: Start with a Political Program

Integrating Engineering and the Human Factor (info@uffmm.org) eJournal uffmm.org ISSN 2567-6458, Nov 23-28, 2020
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

As described in the uffmm eJournal  the wider context of this software project is a generative theory of cultural anthropology [GCA] which is an extension of the engineering theory called Distributed Actor-Actor Interaction [DAAI]. In  the section Case Studies of the uffmm eJournal there is also a section about Python co-learning – mainly
dealing with python programming – and a section about a web-server with
Dragon. This document is part of the Case Studies section.

CONTENT

Applying the original P-V-Pref Document structure to real cases it became clear that the everyday logic behind the classification of facts into problems [P] or  visions [V] follows a kind of logic hidden in the semantic space of the used expressions. This text explains this hidden logic and what this means for our application.

PDF DOCUMENT

VIDEO [DE]

REMARK

(After first presentations of this video)

(Last change: November 28, 2020)

Confusion by different meanings

While the general view of the whole process is quite clear there arose some hot debate about the everyday situation of the experts (here: citizens)  and the concepts ‘reality [R]‘, ‘vision [V] (imagination of a  state which is not yet real)’, ‘problem [P]‘, and ‘preference [Pref]‘. The members of my zevedi-working group (located at the INM (Frankfurt, Hessen, Germany) as well as a citizen from Dieburg (Hessen, Germany) associated with ‘reality’ also the different kinds of emotions being active in a person and they classified an imagination about a future state also as being real in a concrete person. With such a setting of the concepts it became difficult to motivate the logic illustrated in the video. The video — based on the preceding paper — talks about  a vision v, which can turn a reality r into a problem p, and thereby generating a preference Pref = (v,r). A preference can possibly become a trigger of  some change process.

Looking ahead

Before clarifying this discussion let as have a look ahead to the overall change process which constitutes the heart of the komega-software.  Beginning with October 18, 2020 the idea of this overall change process has been described in this blog. Having some given situation S, the komega software allows the construction of change rules X,  which can be applied onto a given situation S and a builtin simulator [sim] will generate a follow up situation S’ like sim(X,S)=S’ — or short: X(S) = S’ –, a process which can be repeated by using the output S’ as new input for a new cycle. At any time of this cyclic process one can ask whether the actual output S’ can be classified as successful. What is called ‘successful’ depends from the applied criteria. For the komega software at least two criteria are used. The most basic one looks to the ectual end state S’ of the simulation and computes the difference between the occurences of vision statements V in S’ and the occurrences of real statements R having been declared at the beginning as problems P as part of the  start situation S. Ideally the real statements classified as problems should have been disappeared and the vision statements should be present.  If the difference is bigger than some before agreed threshold theta  than the actual end state S’ will be classified as a success, as a goal state in the light of the visions of the preferences, which triggered the change process.

Vision statement

In the context of the whole change process a vision statement is an expression e associated with some everyday language L and which describes in the understanding of the experts a state, which is in our mindes conceivable, imaginable, which is not given as a real state, but can eventually  become a real state in some future. This disctinction presupposes that the expert can distinguish between an idea in his consciousness which is associated with some real state outside his consciousness — associated with a real state — and an idea, which is only inside his consciousness — associated with an imaginated state –.  Looking from a second person to the expert this second person can observe the body of the expert and the world surrounding the body and can speak of the real world and the real body of the expert, but the inner states of the expert are hidden for this second person. Thus from the point of view of this second person there are no real imaginations, no real future states. But the expert can utter some expression e which has a meaning describing some state, which as such is not yet real, but which possibly could become real if one would change the actual reality (the actual everyday life, the actual city …) accordingly.  Thus a vision statement is understood here as an expression e from the everyday language L uttered by some expert having a meaning which can be understood by the other persons describing some imginated state, which is not yet real but could eventually become real in some future ahead.

Creating problems, composing preferences

If at least one vision statement v is known by some experts, then it can happen, that an expert does relate this vision with some given reality r as part of the everyday life or with some absent reality r. Example: if an expert classifies some part of the city as having too much traffic (r1) and he has the vision of changing this into a situation where the traffic is lowered down by X% (v1), then this vision statement v1 can help to understand other experts to interpret the reality r1 in the light of the visiin v1 as a problem v1(r1) = p1. Classifying some reality r1 into a problem p1 is understood in the context of the komega software as making the reality r1 a candidate for a possible change in the sense that r1 should be replaced by v1. Having taken this stance — seeing the reality r1 as a problem p1 by the vision v1 –, than the experts  have created a so-called preference Pref = (v1, p1) saying that the experts are preferring the imaginated possibly future state v1 more than the actual problem p1.

There is the special case, that an expert has uttered a vision statement v but there is no given reality which can be stated in a real statement r. Example: A company thinks that it can produce some vaccine against the  disease Y in two years from now, like  v2=’there is a vaccine against disease Y in yy’. Actually there exists no vaccine, but a disease is attacking the people. Because it is known, that the people can be made immune against the disease by an appropriate vaccine it makes sense to state r2=’There is no vaccine against the disease Y available’. Having the vision v2 this can turn the reality r2 into a problem p2 allowing the preference Pref=(v2,p2).

Triggering actions

If a group of experts generated a vision v — by several and different reaons (including emotions) –, having  associated this with some given eality r, and they decided to generate by v(r)=p  a preference Pr =(v,p),  then it can happen , that these experts decide to start a change process beginning now with the given problem p and ending up with a situation in some future where the problem p disappeared and the vision has become real.

Summing up

The komega software allows the planning and testing of change processes  if the acting experts have at least one preference Pref based on at least one  vision statement v and at least one real statement r.

BITS OF PHILOSOPHY

Shows the framework for the used concepts from the point of view of philosophy
Philosophical point of view

The above video (in German, DE) and the following  lengthy remark after the video how to understand the basic concepts vision statement [v],  real statement [r], problem statement [p], as well as preference [Pref] presuppose both a certain kind of philosophy. This philosophical point of view is outlined above in a simple drawing.

Basically there is a real human person (an actor) with a real brain embedded in some everyday world. The person can perceive parts of the every day world at every point of time. The most important reference point  in time is the actual moment called NOW.

Inside the brain the human person can generate some cognitive structure triggered by perception, by  memory and by some thinking.  Having learned some everyday language L the human person can map the cognitive structure into an expression E associated with the language L. If the cognitive structure correlates with some real situation outside the body then the meaning of the expression E is classified as being a real statement, here named E1.  But the brain can generate also cognitive structures and mapping these in expressions E without being actually correlated with some real situation outside. Such a statement is here called a vision statement, here named E2. A vision statement can eventually become correlated with some real situation outside in some future. In that case the vision statement transforms into a real statement E2, while the before mentioned real statement E1 can lose its correlation with a real situation.

FURTHER DISCUSSIONS

For further discussions have a look to this page too.

 

KOMEGA REQUIREMENTS: Multi Group Management

Integrating Engineering and the Human Factor (info@uffmm.org) eJournal uffmm.org ISSN 2567-6458, Nov 12 – Dec 13, 2020
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

As described in the uffmm eJournal  the wider context of this software project is a generative theory of cultural anthropology [GCA] which is an extension of the engineering theory called Distributed Actor-Actor Interaction [DAAI]. In  the section Case Studies of the uffmm eJournal there is also a section about Python co-learning – mainly
dealing with python programming – and a section about a web-server with
Dragon. This document is part of the Case Studies section.

CONTENT

Introducing the management of multiple groups working with different projects in parallel.

Update from Dec 10-13, 2020:

During the last sessions with different groups some first procedure shows up like a recipe to prepare the start of a development process using the komega-SW (See the this whole page and some others).

Supported by the complexity planning software — working title ‘komega-SW’ — different groups of experts, which are using one of the possible everyday languages can proceed with the following steps:

  1. They have to decide where — location, city, region, …[SPC] — they want to realize a change process.
  2. Additionally they have to agree about an intended time-frame [TF] within which this change process should happen.
  3. Every intended change process requires at least one vision [V] and some related given realities [R] which will be affected by the change process. There can be many visions in parallel. The visions can also be organized in conceptual hierarchies with most abstract visions on top which then are extended by more concrete visions as far as wanted.
  4. As soon as given realities are associated with a vision these realities can be classified as  problems [P], this means realities which are candidates of an intended change.
  5. The announced visions and the defined problems imply a certain set of actors [A], which will be necessary for the change process.
  6. To start the change process one has finally to define an inital  state, the start state [S_start], which includes the set of realities as a subset, which have  before been declared as problems.
  7. The preceding figure shows the relation between the start situation S_Start as some part of the real everyday world, the kernel state S_Kernel is characterized by those real facts which are are associated with some vision, and then the remaining facts S_Remain which will be enclosed in the start state S_Start beyond the kernel facts.
Update from December 9, 2020:

An Overall Tutorial [DE ] and Example 1 for the German Students in the Modul ‘Kommunalplanung & Gamification. Labor für mehr Bürgerbeteiligung’

tutorial-1-complmngr-v2 (Last change: December 9, 2020)

tutorial-2-complmngr-v1 (Last change: December 9, 2020)

 

Update from December 5, 2020

(This update has been highly influenced by discussions with Philipp Westermeier and Athene Sorokowski from the ZEVEDIINM Team).

The above figure shows a slightly renewed version of the komega SW as a whole. The arguments for this change are discussed elsewhere.

As You can detect by inspection of the new and the old version (figure below) there are three regions in the figure which have been changed: (1) the first module entitled ‘V-R/P-Pref’, (2) the second module entitled ‘Ss’, and (3) the last module entitled ‘EVAL’.

  1. In the original version the concepts ‘Vision’, ‘Problem’ as well as ‘Preferences’ have not been defined very  sharply. This deficiency has been revealed during the first tests. Several discussions have led to the new version now incorporated in the overall concept. According to the mentioned discussion these concepts are now defined as follows: an expert living in some everyday world can use expressions to refer to parts of this reality; these expressions are now called real statements [R]. Such an expert can furthermore use expressions which have no relationship to some known part of the given reality; these expressions are called here vision statements [V] because they are actually non-real. An expert can decide for himself/ herself/ x-self, that such a vision statement in a possible future perhaps can become real. A vision statement would in such a possible future then become turned  into a real statement. An expert having a vision as well as  a real statement can furthermore associate the vision and the real statement in the way of a preference like V > R, saying that he/she/x prefers V before R. After such a decision the reality R as part of the preference V > R is no longer yet a neutral part of reality but appears in the light of the preferred vision V as a problem [P] which can become the object of some change. Whether such a change indeed will happen  depends again from the decision of the expert, to start a change process leading from some initial state S_start to some goal state S_goal. After having defined a vision statement and associated with this vision statement some real statements the expert has to announce all the actors [A] (individual persons, groups, institutions, …) which are involved in the real statement as well in the vision statement.
  2. If the expert decides to start a change process with an initial state S_start then he has to include into this initial state S_start at least all the realities R_i which are occurring in a preference V_i > R_i as  R=∑R_i. Usually the initial state S_start will include other real statements too because the problematic parts of the reality are usually embedded in a richer context with other facts.
  3. If in the described way the expert has explicitly introduced  Visions V and problems P then this allows that the evaluation module EVAL can use these expressions in the following  way: embedded within the simulation process [SIM] the simulator can check after each cycle whether the actual state S contains already vision statements as real statements and that some — or all — of the problem statements have disappeared. According to some predefined threshold θ it is possible then to give a judgment whether the actual state S is already a goal state S_goal or not. A simple formula could be: IF ∑V_i – ∑P_i > θ THEN (S is_goal) is TRUE.
  4. The other change happened in the second evaluation mode:  in this second mode not only the final state of a simulation process will be judged to be a goal state but the whole process will also be weighted! This means that in the vision there can be global visions like being sustainable, but such global  visions can/ must be differentiated with regard to more concrete measures like ‘CO2-free’ or ‘recycling of resources’ something like this. If such visions are defined than the change rules [X] can be enhanced with parameters measuring properties of states and changes with regard to these visions. During evaluation one can then check the final state as described above but one can include also the different parameters measuring important properties of the process. Then perhaps ‘at a first glance’ a state can appear as if it is a goal state, but by including the more fine grained parameters it can turn out, that some of the requirement parameters for the sustainable vision are not satisfied (nice cars bad a worse CO2 balance).
Version before December 5, 2020

PDF DOCUMENT

requirements-Multi-Group-Management12nov2020

PDF DOCUMENT [DE]

A new and enlarged document to serve the needs of some German Audience.

fue-zim-omnikernel

 

KOMEGA REQUIREMENTS: Interactive Simulations

Integrating Engineering and the Human Factor (info@uffmm.org) eJournal uffmm.org ISSN 2567-6458, Nov 12, 2020
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

As described in the uffmm eJournal  the wider context of this software project is a generative theory of cultural anthropology [GCA] which is an extension of the engineering theory called Distributed Actor-Actor Interaction [DAAI]. In  the section Case Studies of the uffmm eJournal there is also a section about Python co-learning – mainly
dealing with python programming – and a section about a web-server with
Dragon. This document is part of the Case Studies section.

CONTENT

Introducing the interactive mode of simulation besides the existing
passive mode.

PDF DOCUMENT

requirements-interactive-simulations12nov2020

From Men to Philosophy, to Empirical Sciences, to Real Systems. A Conceptual Network

Integrating Engineering and the Human Factor (info@uffmm.org)
eJournal uffmm.org ISSN 2567-6458, Nov 8, 2020
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

As described in the uffmm eJournal  the wider context of this software project is a generative theory of cultural anthropology [GCA] which is an extension of the engineering theory called Distributed Actor-Actor Interaction [DAAI]. In  the section Case Studies of the uffmm eJournal there is also a section about Python co-learning – mainly
dealing with python programming – and a section about a web-server with
Dragon. This document is part of the Case Studies section.

DAILY LIFE

In daily life we experience today a multitude of perspectives in all areas. While our bodies are embedded in real world scenarios our minds are filled up with perceptions, emotions, ideas, memories of all kinds. What links us to each other is language. Language gives us the power to overcome the isolation of our individual brains located in  individual bodies. And by this, our language, we can distribute and share the inner states of our brains, pictures of life as we see it. And it is this open web of expressions which spreads to the air, to the newspapers and books, to the data bases in which the different views of the world are manifested.

SORTING IDEAS SCIENTIFICALLY

While our bodies touching reality outside the bodies, our brains are organizing different kinds of order, finally expressed — only some part of it — in expressions of some language. While our daily talk is following mostly automatically some naive patterns of ordering does empirical science try to order the expressions more consciously following some self-defined rules called methods, called scientific procedures to enable transparency, repeatability, decidability of the hypothesized truth of is symbolic structures.

But because empirical science wants to be rational by being transparent, repeatable, measurable, there must exist an open discourse which is dealing with science as an object: what are the ingredients of science? Under which conditions can science work? What does it mean to ‘measure’ something? And other questions like these.

PHILOSOPHY OF SCIENCE

That discipline which is responsible for such a discourse about science is not science itself but another instance of thinking and speaking which is called Philosophy of Science.  Philosophy of science deals with all aspects of science from the outside of science.

PHILOSOPHY

Philosophy of Science dealing with empirical sciences as an object has a special focus and  it can be reflected too from another point of view dealing with Philosophy of Science as an object. This relationship reflects a general structure of human thinking: every time we have some object of our thinking we are practicing a different point of view talking about the actual object. While everyday thinking leads us directly to Philosophy as our active point of view  an object like empirical science does allow an intermediate point of view called Philosophy of Science leading then to Philosophy again.

Philosophy is our last point of reflection. If we want to reflect the conditions of our philosophical thinking than our thinking along with the used language tries to turn back on itself  but this is difficult. The whole history of Philosophy shows this unending endeavor as a consciousness trying to explain itself by being inside itself. Famous examples of this kind of thinking are e.g. Descartes, Kant, Fichte, Schelling, Hegel, and Husserl.

These examples show there exists no real way out.

PHILOSOPHY ENHANCED BY EMPIRICAL SCIENCES ? !

At a first glance it seems contradictory that Philosophy and Empirical Sciences could work ‘hand in hand’. But history has shown us, that this is to a certain extend possible; perhaps it is a major break through for the philosophical understanding of the world, especially also of men themselves.

Modern empirical sciences like Biology and Evolutionary Biology in cooperation with many other empirical disciplines have shown us, that the actual biological systems — including homo sapiens — are products of a so-called evolutionary process. And supported by modern empirical disciplines like Ethology, Psychology, Physiology, and Brain Sciences we could gain some first knowledge how our body works, how our brain, how our observable behavior is connected to this body and its brain.

While  Philosopher like Kant or Hegel could  investigate their own thinking only from the inside of their consciousness, the modern empirical sciences can investigate the human thinking from the outside. But until now there is a gap: We have no elaborated theory about the relationship between the inside of the consciousness and the outside knowledge about body and brain.

Thus what we need is a hybrid  theory mapping the inside to the outside and revers.  There are some first approaches headed under labels like Neuro-Psychology or Neuro-Phenomenology, but these are not yet completely clarified in their methodology in their relationship to Philosophy.

If one can describe to some extend the Phenomena of the consciousness from the inside as well as the working of the brain translated to its behavioral properties, then one can start first mappings like those, which have been used in this blog to establish  the theory for the komega software.

SOCIOLOGY

Sociology is only one empirical discipline  between many others. Although the theory of this blog is using many disciplines simultaneously Sociology is of special interest because it is that kind of empirical disciplines which is explicitly dealing with human societies with subsystems called cities.

The komega software which we are developing is understood here as enabling a system of interactions as part of a city understood as a system. If we understand Sociology as an empirical science according to some standard view of empirical science then it is possible to describe a city as an input-output system whose dynamics can become influenced by this komega software if citizens are using this software as part of their behavior.

STANDARD VIEW OF EMPIRICAL SCIENCE

Without some kind of a Standard View of Empirical Science it is not possible to design a discipline — e.g. Sociology — as an empirical discipline. Although it seems that everybody thinks that we have  such a ‘Standard View of Empirical Science’, in the real world of today one must state that we do not have such a view. In the 80ties of the20th century it looked for some time as if  we have it, but if you start searching the papers, books and schools today You will perceive a very fuzzy field called Philosophy of Science and within the so-called empirical sciences you will not found any coherent documented view of a ‘Standard View of Empirical Science’.

Because it is difficult to see how a process can  look like which enables such a ‘Standard View of Empirical Science’ again, we will try to document the own assumptions for our theory as good as possible. Inevitably this will mostly  have the character of only a ‘fragment’, an ‘incomplete outline’. Perhaps there will again be a time where sciences is back to have a commonly accepted view how  science should look like to be called empirical science.

 

 

 

 

KOMEGA REQUIREMENTS: Basic Version with optional on-demand Computations by the Computer

Integrating Engineering and the Human Factor (info@uffmm.org) eJournal uffmm.org ISSN 2567-6458, Nov 15, 2020

Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

As described in the uffmm eJournal  the wider context of this software project is a generative theory of cultural anthropology [GCA] which is an extension of the engineering theory called Distributed Actor-Actor Interaction [DAAI]. In  the section Case Studies of the uffmm eJournal there is also a section about Python co-learning – mainly
dealing with python programming – and a section about a web-server with
Dragon. This document is part of the Case Studies section.

CONTENT

Introducing a new general interface to transfer messages to the simulator as computer to compute explicitly some functions.

PDF DOCUMENT

requirements-inductive-semantics-27Oct2020

VIDEO [de]

This video explains in German the new ‘computation on-demand’ element of the change rules. More details are explained in the preceding English Text of the PDF document. As next step this idea will be implemented and it will be shown with another video, how this idea looks like in action.

VIDEO 2 [DE]

Explains  the first Problem-Vision-Preferences Module and makes some remarks how this is related  to the final evaluation module.

komega-v09b: from minimal to basic, first step

Journal: uffmm.org,
ISSN 2567-6458, Oct 14 until  Oct-21, 2020
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email:gerd@doeben-henisch.de

ABSTRACT

This is the first step from the minimal version v08e into the direction of a basic version v09x. In v09b you can integrate multiple state descriptions into one state S and multiple rule documents into one X and then you can use these unified documents (S,X) for your simulation.

PDF Documents

The main program:
sourcecode-komega-v09b
The imported classes:
sourcecode-kcv9b

(If You want to use these sources on Windows 10 then you have to edit the last line of the classes document following the instruction there)

(During the next weeks — somewhere after 9.December 2020 — the whole software will be accessible by an interactive webpage)

KOMEGA REQUIREMENTS: From the minimal to the basic version

ISSN 2567-6458, 18.October  2020
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

As described in the uffmm eJournal  the wider context of this software project is a generative theory of cultural anthropology [GCA] which is an extension of the engineering theory called Distributed Actor-Actor Interaction [DAAI]. In  the section Case Studies of the uffmm eJournal there is also a section about Python co-learning – mainly
dealing with python programming – and a section about a web-server with
Dragon. This document is part of the Case Studies section.

CONTENT

Here we present the ideas how to extend the minimal version to a first basic version. At least two more advanced levels will follow.

VIDEO (EN)

(Last change: Oct 17, 2020)

VIDEO(DE)

(last change: Oct 18, 2020)

komega-v08e. First complete minimal version with tests

Journal: uffmm.org,
ISSN 2567-6458,Oct 14 until  Oct-15, 2020
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email:gerd@doeben-henisch.de

ABSTRACT

This is the first complete minimal version together with two tests with the German language  as well as with the English language. From now on this ‘starting point’ will be improved step wise until some point in the future.

PDF Documents

PYTHON CODE MAIN FILE

This file is importing the file kcv8e

komega-v08e-main

(Last change: Oct 11, 2020)

PYTHON USED CLASSES

kcv8e-classes

This file is importing the ‘shelve’ module. The ‘shelve’ module has a different back end with linux or windows. See the remark at the end of the kcv8e file.

(Last change: Oct 15, 2020)

EXAMPLE with GERMAN language

test-komega-v08e-GermanExample1

(Last change Oct 15,2020)

EXAMPLE with ENGLISH language

test-komega-v08e-EnglishExample1

(Last change: Oct 15, 2020)

LINUX – WINDOWS10

(Last change: Oct 13,2020)

If you want to run the program komega-v08e.py which is importing kcv8e.py which in turn is importing the shelve modul under Windows 10 then you have in the file kcv8e.py the last line, where the storage objects initializes three databases:

LINUX:

st=Storage(‘STAT1′,’RULE1′,’PV1’)

WINDOWS10:

st=Storage(‘STAT1.dat’,’RULE1.dat’,’PV1.dat’)

The reason for this is that the shelve modul is using internally a db-interface which can be differently be implemented on different systems. For windows you need this special Postfix ‘.dat’ to indicate the windows-specific implementation.

VIDEOS

These videos show the generation of cases

(Protocol of first live session, see video)

GerdIstHungrig1

(Recorded: Oct 15, 2020 8:30am)

(Protocol 2nd live session, see video)

test-komega-v08e-GermanExample2

(recorded: Oct 15, 2020 11:30 am)

komega-v08a. First complete version with simulation

Journal: uffmm.org,
ISSN 2567-6458, Sept-16, 2020
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email:gerd@doeben-henisch.de

ABSTRACT

A first minimal version of a simulator is working. Another  solution  in version   komega-v07a was too bad and has been thrown in the ‘trash’ and now we have komega-v08a. You can get the real idea in a nucleus. Many things have to be improved and will be improved (not before End of October :-)). An important improvement was the inclusion of set theoretical data structures and operators.

SOURCE CODE AS PDF

komega-v08a

KOMEGA REQUIREMENTS No.4, Version 5. Basic Application Scenario

ISSN 2567-6458, 13.September  2020
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

As described in the uffmm eJournal  the wider context of this software project is a generative theory of cultural anthropology [GCA] which is an extension of the engineering theory called Distributed Actor-Actor Interaction [DAAI]. In  the section Case Studies of the uffmm eJournal there is also a section about Python co-learning – mainly
dealing with python programming – and a section about a web-server with
Dragon. This document will be part of the Case Studies section.

PDF DOCUMENT

requirements-no4-v5-13Sept2020

The only change to the preceding version is a short description of the first simple simulator cycle which will be used  in the parallel python program.