Category Archives: time

Pain does not replace the truth …

Time: Oct 18, 2023 — Oct 24, 2023)
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.d
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CONTEXT

This post is part of the uffmm science blog. It is a translation from the German source: https://www.cognitiveagent.org/2023/10/18/schmerz-ersetzt-nicht-die-wahrheit/. For the translation I have used chatGPT4 and deepl.com. Because in the text the word ‘hamas’ is occurring, chatGPT didn’t translate a long paragraph with this word. Thus the algorithm is somehow ‘biased’ by a certain kind of training. This is really bad because the following text is offers some reflections about a situation where someone ‘hates’ others. This is one of our biggest ‘disease’ today.

Preface

The Hamas terrorist attack on Israeli citizens on October 7, 2023, has shaken the world. For years, terrorist acts have been shaking our world. In front of our eyes, a is attempting, since 2022 (actually since 2014), to brutally eradicate the entire Ukrainian population. Similar events have been and are taking place in many other regions of the world…

… Pain does not replace the truth [0]…

Truth is not automatic. Making truth available requires significantly more effort than remaining in a state of partial truth.

The probability that a person knows the truth or seeks the truth is smaller than staying in a state of partial truth or outright falsehood.

Whether in a democracy, falsehood or truth predominates depends on how a democracy shapes the process of truth-finding and the communication of truth. There is no automatic path to truth.

In a dictatorship, the likelihood of truth being available is extremely dependent on those who exercise centralized power. Absolute power, however, has already fundamentally broken with the truth (which does not exclude the possibility that this power can have significant effects).

The course of human history on planet Earth thus far has shown that there is evidently no simple, quick path that uniformly leads all people to a state of happiness. This must have to do with humans themselves—with us.

The interest in seeking truth, in cultivating truth, in a collective process of truth, has never been strong enough to overcome the everyday exclusions, falsehoods, hostilities, atrocities…

One’s own pain is terrible, but it does not help us to move forward…

Who even wants a future for all of us?????

[0] There is an overview article by the author from 2018, in which he presents 15 major texts from the blog “Philosophie Jetzt” ( “Philosophy Now”) ( “INFORMAL COSMOLOGY. Part 3a. Evolution – Truth – Society. Synopsis of previous contributions to truth in this blog” ( https://www.cognitiveagent.org/2018/03/20/informelle-kosmologie-teil-3a-evolution-wahrheit-gesellschaft-synopse-der-bisherigen-beitraege-zur-wahrheit-in-diesem-blog/ )), in which the matter of truth is considered from many points of view. In the 5 years since, society’s treatment of truth has continued to deteriorate dramatically.

Hate cancels the truth


Truth is related to knowledge. However, in humans, knowledge most often is subservient to emotions. Whatever we may know or wish to know, when our emotions are against it, we tend to suppress that knowledge.

One form of emotion is hatred. The destructive impact of hatred has accompanied human history like a shadow, leaving a trail of devastation everywhere it goes: in the hater themselves and in their surroundings.

The event of the inhumane attack on October 7, 2023 in Israel, claimed by Hamas, is unthinkable without hatred.

If one traces the history of Hamas since its founding in 1987 [1,2], then one can see that hatred is already laid down as an essential moment in its founding. This hatred is joined by the moment of a religious interpretation, which calls itself Islamic, but which represents a special, very radicalized and at the same time fundamentalist form of Islam.

The history of the state of Israel is complex, and the history of Judaism is no less so. And the fact that today’s Judaism also contains strong components that are clearly fundamentalist and to which hatred is not alien, this also leads within many other factors at the core to a constellation of fundamentalist antagonisms on both sides that do not in themselves reveal any approaches to a solution. The many other people in Israel and Palestine ‘around’ are part of these ‘fundamentalist force fields’, which simply evaporate humanity and truth in their vicinity. By the trail of blood one can see this reality.

Both Judaism and Islam have produced wonderful things, but what does all this mean in the face of a burning hatred that pushes everything aside, that sees only itself.

[1] Jeffrey Herf, Sie machen den Hass zum Weltbild, FAZ 20.Okt. 23, S.11 (Abriss der Geschichte der Hamas und ihr Weltbild, als Teil der größeren Geschichte) (Translation:They make hatred their worldview, FAZ Oct. 20, 23, p.11 (outlining the history of Hamas and its worldview, as part of the larger story)).

[2] Joachim Krause, Die Quellen des Arabischen Antisemitismus, FAZ, 23.10.2023,p.8 (This text “The Sources of Arab Anti-Semitism” complements the account by Jeffrey Herf. According to Krause, Arab anti-Semitism has been widely disseminated in the Arab world since the 1920s/ 30s via the Muslim Brotherhood, founded in 1928).

A society in decline

When truth diminishes and hatred grows (and, indirectly, trust evaporates), a society is in free fall. There is no remedy for this; the use of force cannot heal it, only worsen it.

The mere fact that we believe that lack of truth, dwindling trust, and above all, manifest hatred can only be eradicated through violence, shows how seriously we regard these phenomena and at the same time, how helpless we feel in the face of these attitudes.

In a world whose survival is linked to the availability of truth and trust, it is a piercing alarm signal to observe how difficult it is for us as humans to deal with the absence of truth and face hatred.

Is Hatred Incurable?

When we observe how tenaciously hatred persists in humanity, how unimaginably cruel actions driven by hatred can be, and how helpless we humans seem in the face of hatred, one might wonder if hatred is ultimately not a kind of disease—one that threatens the hater themselves and, particularly, those who are hated with severe harm, ultimately death.

With typical diseases, we have learned to search for remedies that can free us from the illness. But what about a disease like hatred? What helps here? Does anything help? Must we, like in earlier times with people afflicted by deadly diseases (like the plague), isolate, lock away, or send away those who are consumed by hatred to some no man’s land? … but everyone knows that this isn’t feasible… What is feasible? What can combat hatred?

After approximately 300.000 years of Homo sapiens on this planet, we seem strangely helpless in the face of the disease of hatred.

What’s even worse is that there are other people who see in every hater a potential tool to redirect that hatred toward goals they want to damage or destroy, using suitable manipulation. Thus, hatred does not disappear; on the contrary, it feels justified, and new injustices fuel the emergence of new hatred… the disease continues to spread.

One of the greatest events in the entire known universe—the emergence of mysterious life on this planet Earth—has a vulnerable point where this life appears strangely weak and helpless. Throughout history, humans have demonstrated their capability for actions that endure for many generations, that enable more people to live fulfilling lives, but in the face of hatred, they appear oddly helpless… and the one consumed by hatred is left incapacitated, incapable of anything else… plummeting into their dark inner abyss…


Instead of hatred, we need (minimally and in outline):

  1. Water: To sustain human life, along with the infrastructure to provide it, and individuals to maintain that infrastructure. These individuals also require everything they need for their own lives to fulfill this task.
  2. Food: To sustain human life, along with the infrastructure for its production, storage, processing, transportation, distribution, and provision. Individuals are needed to oversee this infrastructure, and they, too, require everything they need for their own lives to fulfill this task.
  3. Shelter: To provide a living environment, including the infrastructure for its creation, provisioning, maintenance, and distribution. Individuals are needed to manage this provision, and they, too, require everything they need for their own lives to fulfill this task.
  4. Energy: For heating, cooling, daily activities, and life itself, along with the infrastructure for its generation, provisioning, maintenance, and distribution. Individuals are needed to oversee this infrastructure, and they, too, require everything they need for their own lives to fulfill this task.
  5. Authorization and Participation: To access water, food, shelter, and energy. This requires an infrastructure of agreements, and individuals to manage these agreements. These individuals also require everything they need for their own lives to fulfill this task.
  6. Education: To be capable of undertaking and successfully completing tasks in real life. This necessitates individuals with enough experience and knowledge to offer and conduct such education. These individuals also require everything they need for their own lives to fulfill this task.
  7. Medical Care: To help with injuries, accidents, and illnesses. This requires individuals with sufficient experience and knowledge to offer and provide medical care, as well as the necessary facilities and equipment. These individuals also require everything they need for their own lives to fulfill this task.
  8. Communication Facilities: So that everyone can receive helpful information needed to navigate their world effectively. This requires suitable infrastructure and individuals with enough experience and knowledge to provide such information. These individuals also require everything they need for their own lives to fulfill this task.
  9. Transportation Facilities: So that people and goods can reach the places they need to go. This necessitates suitable infrastructure and individuals with enough experience and knowledge to offer such infrastructure. These individuals also require everything they need for their own lives to fulfill this task.
  10. Decision Structures: To mediate the diverse needs and necessary services in a way that ensures most people have access to what they need for their daily lives. This requires suitable infrastructure and individuals with enough experience and knowledge to offer such infrastructure. These individuals also require everything they need for their own lives to fulfill this task.
  11. Law Enforcement: To ensure disruptions and damage to the infrastructure necessary for daily life are resolved without creating new disruptions. This requires suitable infrastructure and individuals with enough experience and knowledge to offer such services. These individuals also require everything they need for their own lives to fulfill this task.
  12. Sufficient Land: To provide enough space for all these requirements, along with suitable soil (for water, food, shelter, transportation, storage, production, etc.).
  13. Suitable Climate
  14. A functioning ecosystem.
  15. A capable scientific community to explore and understand the world.
  16. Suitable technology to accomplish everyday tasks and support scientific endeavors.
  17. Knowledge in the minds of people to understand daily events and make responsible decisions.
  18. Goal orientations (preferences, values, etc.) in the minds of people to make informed decisions.
  19. Ample time and peace to allow these processes to occur and produce results.
  20. Strong and lasting relationships with other population groups pursuing the same goals.
  21. Sufficient commonality among all population groups on Earth to address their shared needs where they are affected.
  22. A sustained positive and constructive competition for those goal orientations that make life possible and viable for as many people on this planet (in this solar system, in this galaxy, etc.) as possible.
  23. The freedom present within the experiential world, included within every living being, especially within humans, should be given as much room as possible, as it is this freedom that can overcome false ideas from the past in the face of a constantly changing world, enabling us to potentially thrive in the world of the future.

POPPER and EMPIRICAL THEORY. A conceptual Experiment


eJournal: uffmm.org
ISSN 2567-6458, 12.March 22 – 16.March 2022, 11:20 h
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 outline the concept of an empirical theory based on a text from Popper 1971. In his article Popper points to a minimal structure of what he is calling an empirical theory. A closer investigation of his texts reveals many questions which should be clarified for a more concrete application of his concept of an empirical theory.

In this post it will be attempted to elaborate the concept of an empirical theory more concretely from a theoretical point of view as well as from an application point of view.

A Minimal Concept of an Empirical Theory

The figure shows the process of (i) observing phenomena, (ii) representing these in expressions of some language L, (iii) elaborating conjectures as hypothetical relations between different observations, (iv) using an inference concept to deduce some forecasts, and (v) compare these forecasts with those observations, which are possible in an assumed situation.

Empirical Basis

As starting point as well as a reference for testing does Popper assume an ’empirical basis’. The question arises what this means.

In the texts examined so far from Popper this is not well described. Thus in this text some ‘assumptions/ hypotheses’ will be formulated to describe some framework which should be able to ‘explain’ what an empirical basis is and how it works.

Experts

Those, who usually are building theories, are scientists, are experts. For a general concept of an ’empirical theory’ it is assumed here that every citizen is a ‘natural expert’.

Environment

Natural experts are living in ‘natural environments’ as part of the planet earth, as part of the solar system, as part of the whole universe.

Language

Experts ‘cooperate’ by using some ‘common language’. Here the ‘English language’ is used; many hundreds of other languages are possible.

Shared Goal (Changes, Time, Measuring, Successive States)

For cooperation it is necessary to have a ‘shared goal’. A ‘goal’ is an ‘idea’ about a possible state in the ‘future’ which is ‘somehow different’ to the given actual situation. Such a future state can be approached by some ‘process’, a series of possible ‘states’, which usually are characterized by ‘changes’ manifested by ‘differences’ between successive states. The concept of a ‘process’, a ‘sequence of states’, implies some concept of ‘time’. And time needs a concept of ‘measuring time’. ‘Measuring’ means basically to ‘compare something to be measured’ (the target) with ‘some given standard’ (the measuring unit). Thus to measure the height of a body one can compare it with some object called a ‘meter’ and then one states that the target (the height of the body) is 1,8 times as large as the given standard (the meter object). In case of time it was during many thousand years customary to use the ‘cycles of the sun’ to define the concept (‘unit’) of a ‘day’ and a ‘night’. Based on this one could ‘count’ the days as one day, two days, etc. and one could introduce further units like a ‘week’ by defining ‘One week compares to seven days’, or ‘one month compares to 30 days’, etc. This reveals that one needs some more concepts like ‘counting’, and associated with this implicitly then the concept of a ‘number’ (like ‘1’, ‘2’, …, ’12’, …) . Later the measuring of time has been delegated to ‘time machines’ (called ‘clocks’) producing mechanically ‘time units’ and then one could be ‘more precise’. But having more than one clock generates the need for ‘synchronizing’ different clocks at different locations. This challenge continues until today. Having a time machine called ‘clock’ one can define a ‘state’ only by relating the state to an ‘agreed time window’ = (t1,t2), which allows the description of states in a successive timely order: the state in the time-window (t1,t2) is ‘before’ the time-window (t2,t3). Then one can try to describe the properties of a given natural environment correlated with a certain time-window, e.g. saying that the ‘observed’ height of a body in time-window w1 was 1.8 m, in a later time window w6 the height was still 1.8 m. In this case no changes could be observed. If one would have observed at w6 1.9 m, then a difference is occurring by comparing two successive states.

Example: A County

Here we will assume as an example for a natural environment a ‘county’ in Germany called ‘Main-Kinzig Kreis’ (‘Kreis’ = ‘county’), abbreviated ‘MKK’. We are interested in the ‘number of citizens’ which are living in this county during a certain time-window, here the year 2018 = (1.January 2018, 31.December 2018). According to the statistical office of the state of Hessen, to which the MKK county belongs, the number of citizens in the MKK during 2018 was ‘418.950’.(cf. [2])

Observing the Number of Citizens

One can ask in which sense the number ‘418.950’ can be understood as an ‘observation statement’? If we understand ‘observation’ as the everyday expression for ‘measuring’, then we are looking for a ‘procedure’ which allows us to ‘produce’ this number ‘418.950’ associated with the unit ‘number of citizens during a year’. As everybody can immediately realize no single person can simply observe all citizens of that county. To ‘count’ all citizens in the county one had to ‘travel’ to all places in the county where citizens are living and count every person. Such a travelling would need some time. This can easily need more than 40 years working 24 hours a day. Thus, this procedure would not work. A different approach could be to find citizens in every of the 24 cities in the MKK [1] to help in this counting-procedure. To manage this and enable some ‘quality’ for the counting, this could perhaps work. An interesting experiment. Here we ‘believe’ in the number of citizens delivered by the statistical office of the state of Hessen [2], but keeping some reservation for the question how ‘good’ this number really is. Thus our ‘observation statement’ would be: “In the year 2018 418.950 citizens have been counted in the MKK (according to the information of the statistical office of the state of Hessen)” This observation statement lacks a complete account of the procedure, how this counting really happened.

Concrete and Abstract Words

There are interesting details in this observation statement. In this observation statement we notice words like ‘citizen’ and ‘MKK’. To talk about ‘citizens’ is not a talk about some objects in the direct environment. What we can directly observe are concrete bodies which we have learned to ‘classify’ as ‘humans’, enriched for example with ‘properties’ like ‘man’, ‘woman’, ‘child’, ‘elderly person’, neighbor’ and the like. Bu to classify someone as a ‘citizen’ deserves knowledge about some official procedure of ‘registering as a citizen’ at a municipal administration recorded in some certified document. Thus the word ‘citizen’ has a ‘meaning’ which needs some ‘concrete procedure to get the needed information’. Thus ‘citizen’ is not a ‘simple word’ but a ‘more abstract word’ with regard to the associated meaning. The same holds for the word ‘MKK’ short for ‘Main-Kinzig Kreis’. At a first glance ‘MKK’ appears as a ‘name’ for some entity. But this entity cannot directly be observed too. One component of the ‘meaning’ of the name ‘MKK’ is a ‘real geographical region’, whose exact geographic extensions have been ‘measured’ by official institutions marked in an ‘official map’ of the state of Hessen. This region is associated with an official document of the state of Hessen telling, that this geographical region has to be understood s a ‘county’ with the name MKK. There exist more official documents defining what is meant with the word ‘county’. Thus the word ‘MKK’ has a rather complex meaning which to understand and to check, whether everything is ‘true’, isn’t easy. The author of this post is living in the MKK and he would not be able to tell all the details of the complete meaning of the name ‘MKK’.

First Lessons Learned

Thus one can learn from these first considerations, that we as citizens are living in a natural environment where we are using observation statements which are using words with potentially rather complex meanings, which to ‘check’ deserves some serious amount of clarification.

Conjectures – Hypotheses

Changes

The above text shows that ‘observations as such’ show nothing of interest. Different numbers of citizens in different years have no ‘message’. But as soon as one arranges the years in a ‘time line’ according to some ‘time model’ the scene is changing: if the numbers of two consecutive years are ‘different’ then this ‘difference in numbers’ can be interpreted as a ‘change’ in the environment, but only if one ‘assumes’ that the observed phenomena (the number of counted citizens) are associated with some real entities (the citizens) whose ‘quantity’ is ‘represented’ in these numbers.[5]

And again, the ‘difference between consecutive numbers’ in a time line cannot be observed or measured directly. It is a ‘second order property’ derived from given measurements in time. Such a 2nd order property presupposes a relationship between different observations: they ‘show up’ in the expressions (here numbers), but they are connected back in the light of the agreed ‘meaning’ to some ‘real entities’ with the property ‘overall quantity’ which can change in the ‘real setting’ of these real entities called ‘citizens’.

In the example of the MKK the statistical office of the state of Hessen computed a difference between two consecutive years which has been represented as a ‘growth factor’ of 0,4%. This means that the number of citizens in the year 2018 will increase until the year 2019 as follows: number-citizens(2019) = number-citizens(2018) + (number of citizens(2018) * growth-factor). This means number-citizens(2019) =418.950 + (418.950 * 0.004) = 418.950 + 1.675,8 = 420.625,8

Applying change repeatedly

If one could assume that the ‘growth rate’ would stay constant through the time then one could apply the growth rate again and again onto the actual number of citizens in the MKK every year. This would yield the following simple table:

YearNumberGrowth Rate
2018418.950,00,0040
2019420.625,80
2020422.308,30
2021423.997,54
2022425.693,53
2023427.396,30
Table: Simplified description of the increase of the number of citizens in the Main-Kinzig county in Germany with an assumed growth rate of 0,4% per year.

As we know from reality an assumption of a fixed growth rate for complex dynamic systems is not very probable.

Theory

Continuing the previous considerations one has to ask the question, how the layout of a ‘complete empirical theory’ would look like?

As I commented in the preceding post about Popper’s 1971 article about ‘objective knowledge’ there exists today no one single accepted framework for a formalized empirical theory. Therefore I will stay here with a ‘bottom-up’ approach using elements taken from everyday reasoning.

What we have until now is the following:

  1. Before the beginning of a theory building process one needs a group of experts being part of a natural environment using the same language which share a common goal which they want to enable.
  2. The assumed natural environment is assumed from the experts as being a ‘process’ of consecutive states in time. The ‘granularity’ of the process depends from the used ‘time model’.
  3. As a starting point they collect a set of statements talking about those aspects of a ‘selected state’ at some time t which they are interested in.
  4. This set of statements describes a set of ‘observable properties’ of the selected state which is understood as a ‘subset’ of the properties of the natural environment.
  5. Every statement is understood by the experts as being ‘true’ in the sense, that the ‘known meaning’ of a statement has an ‘observable counterpart’ in the situation, which can be ‘confirmed’ by each expert.
  6. For each pair of consecutive states it holds that the set of statements of each state can be ‘equal’ or ‘can show ‘differences’.
  7. A ‘difference’ between sets of statements can be interpreted as pointing to a ‘change in the real environment’.[5]
  8. Observed differences can be described by special statements called ‘change statements’ or simply ‘rules’.
  9. A change statement has the format ‘IF a set of statements ST* is a subset of the statements ST of a given state S, THEN with probability p, a set of statements ST+ will be added to the actual state S and a set of statements ST- will be removed from the statements ST of a given state S. This will result in a new succeeding state S* with the representing statements ST – (ST-) + (ST+) depending from the assumed probability p.
  10. The list of change statements is an ‘open set’ according to the assumption, that an actual state is only a ‘subset’ of the real environment.
  11. Until now we have an assumed state S, an assumed goal V, and an open set of change statements X.
  12. Applying change statements to a given state S will generate a new state S*. Thus the application of a subset X’ of the open set of change statements X onto a given state S will here be called ‘generating a new state by a procedure’. Such a state-generating-procedure can be understood as an ‘inference’ (like in logic) oder as a ‘simulation’ (like in engineering).[6]
  13. To write this in a more condensed format we can introduce some signs —– S,V ⊩ ∑ X S‘ —– saying: If I have some state S and a goal V then the simulator will according to the change statements X generate a new state S’. In such a setting the newly generated state S’ can be understood as a ‘theorem’ which has been derived from the set of statements in the state S which are assumed to be ‘true’. And because the derived new state is assumed to happen in some ‘future’ ‘after’ the ‘actual state S’ this derived state can also be understood as a ‘forecast’.
  14. Because the experts can change all the time all parts ‘at will’ such a ‘natural empirical theory’ is an ‘open entity’ living in an ongoing ‘communication process’.
Second Lessons Learned

It is interestingly to know that from the set of statements in state S, which are assumed to be empirically true, together with some change statements X, whose proposed changes are also assumed to be ‘true’, and which have some probability P in the domain [0,1], one can forecast a set of statements in the state S* which shall be true, with a certainty being dependent from the preceding probability P and the overall uncertainty of the whole natural environment.

Confirmation – Non-Confirmation

A Theory with Forecasts

Having reached the formulation of an ordinary empirical theory T with the ingredients <S,V,X,⊩ > and the derivation concept S,V ⊩ ∑ X S‘ it is possible to generate theorems as forecasts. A forecast here is not a single statement st* but a whole state S* consisting of a finite set of statements ST* which ‘designate’ according to the ‘agreed meaning’ a set of ‘intended properties’ which need a set of ‘occurring empirical properties’ which can be observed by the experts. These observations are usually associated with ‘agreed procedures of measurement’, which generate as results ‘observation statements’/ ‘measurement statements’.

Within Time

Experts which are cooperating by ‘building’ an ordinary empirical theory are themselves part of a process in time. Thus making observations in the time-window (t1,t2) they have a state S describing some aspects of the world at ‘that time’ (t1,t2). When they then derive a forecast S* with their theory this forecast describes — with some probability P — a ‘possible state of the natural environment’ which is assumed to happen in the ‘future’. The precision of the predicted time when the forecasted statements in S* should happen depends from the assumptions in S.

To ‘check’ the ‘validity’ of such a forecast it is necessary that the overall natural process reaches a ‘point in time’ — or a time window — indicated by the used ‘time model’, where the ‘actual point in time’ is measured by an agreed time machine (mechanical clock). Because there is no observable time without a time machine the classification of a certain situation S* being ‘now’ at the predicted point of time depends completely from the used time machine.[7]

Given this the following can happen: According to the used theory a certain set of statements ST* is predicted to be ‘true’ — with some probability — either ‘at some time in the future’ or in the time-window (t1,t2) or at a certain point in time t*.

Validating Forecasts

If one of these cases would ‘happen’ then the experts would have the statements ST* of their forecast and a real situation in their natural environment which enables observations ‘Obs’ which are ‘translated’ into appropriate ‘observation statements’ STObs. The experts with their predicted statements ST* know a learned agreed meaning M* of their predicted statements ST* as intended-properties M* of ST*. The experts have also learned how they relate the intended meaning M* to the meaning MObs from the observation statements STobs. If the observed meaning MObs ‘agrees sufficiently well’ with the intended meaning M* then the experts would agree in a statement, that the intended meaning M* is ‘fulfilled’/ ‘satisfied’/ ‘confirmed’ by the observed meaning MObs. If not then it would stated that it is ‘not fulfilled’/ ‘not satisfied’/ ‘not confirmed’.

The ‘sufficient fulfillment’ of the intended meaning M* of a set of statements ST* is usually translated in a statement like “The statements ST* are ‘true'”. In the case of ‘no fulfillment’ it is unclear: this can be interpreted as ‘being false’ or as ‘being unclear’: No clear case of ‘being true’ and no clear case of ‘being false’.

Forecasting the Number of Citizens

In the used simple example we have the MKK county with an observed number of citizens in 2018 with 418950. The simple theory used a change statement with a growth factor of 0.4% per year. This resulted in the forecast with the number 420.625 citizens for the year 2019.

If the newly counting of the number of citizens in the years 2019 would yield 420.625, then there would be a perfect match, which could be interpreted as a ‘confirmation’ saying that the forecasted statement and the observed statement are ‘equal’ and therefore the theory seems to match the natural environment through the time. One could even say that the theory is ‘true for the observed time’. Nothing would follow from this for the unknown future. Thus the ‘truth’ of the theory is not an ‘absolute’ truth but a truth ‘within defined limits’.

We know from experience that in the case of forecasting numbers of citizens for some region — here a county — it is usually not so clear as it has been shown in this example.

This begins with the process of counting. Because it is very expensive to count the citizens of all cities of a county this happens only about every 20 years. In between the statistical office is applying the method of ‘forecasting projection’.[9] The state statistical office collects every year ‘electronically’ the numbers of ‘birth’, ‘death’, ‘outflow’, and ‘inflow’ from the individual cities and modifies with these numbers the last real census. In the case of the state of Hessen this was the year 2011. The next census in Germany will happen May 2022.[10] For such a census the data will be collected directly from the registration offices from the cities supported by a control survey of 10% of the population.

Because there are data from the statistical office of the state of Hessen for June 2021 [8:p.9] with saying that the MKK county had 421 936 citizens at 30. June 2021 we can compare this number with the theory forecast for the year 2021 with 423 997. This shows a difference in the numbers. The theory forecast is ‘higher’ than the observed forecast. What does this mean?

Purely arithmetically the forecast is ‘wrong’. The responsible growth factor is too large. If one would ‘adjust’ it in a simplified linear way to ‘0.24%’ then the theory could get a forecast for 2021 with 421 973 (observed: 421 936), but then the forecast for 2019 would be 419 955 (instead of 420 625).

This shows at least the following aspects:

  1. The empirical observations as such can vary ‘a little bit’. One had to clarify which degree of ‘variance’ is due to the method of measurement and therefore this variance should be taken into account for the evaluation of a theoretical forecast.
  2. As mentioned by the statistical office [9] there are four ‘factors’ which influence the final number of citizens in a region: ‘birth’, ‘death’, ‘outflow’, and ‘inflow’. These factors can change in time. Under ‘normal conditions’ the birth-rate and the death-rate are rather ‘stable’, but in case of an epidemic situation or even war this can change a lot. Outflow and inflow are very dynamic depending from many factors. Thus this can influence the growth factor a lot and these factors are difficult to forecast.
Third lessons Learned

Evaluating the ‘relatedness’ of some forecast F of an empirical theory T to the observations O in a given real natural environment is not a ‘clear-cut’ case. The ‘precision’ of such a relatedness depends from many factors where each of these factors has some ‘fuzziness’. Nevertheless as experience shows it can work in a limited way. And, this ‘limited way’ is the maximum we can get. The most helpful contribution of an ‘ordinary empirical theory’ seems to be the forecast of ‘What will happen if we have a certain set of assumptions’. Using such a forecast in the process of the experts this can help to improve to get some ‘informed guesses’ for planning.

Forecast

The next post will show, how this concept of an ordinary empirical theory can be used by applying the oksimo paradigm to a concrete case. See HERE.

Comments

[1] Cities of the MKK-county: 24, see: https://www.wegweiser-kommune.de/kommunen/main-kinzig-kreis-lk

[2] Forecast for development of the number of citizens in the MMK starting with 2018, See: the https://statistik.hessen.de/zahlen-fakten/bevoelkerung-gebiet-haushalte-familien/bevoelkerung/tabellen

[3] Karl Popper, „A World of Propensities“,(1988) and „Towards an Evolutionary Theory of Knowledge“, (1989) in: Karl Popper, „A World of Propensities“, Thoemmes Press, Bristol, (1990, repr. 1995)

[4] Karl Popper, „All Life is Problem Solving“, original a lecture 1991 in German, the first tome published (in German) „Alles Leben ist Problemlösen“ (1994), then in the book „All Life is Problem Solving“, 1999, Routledge, Taylor & Francis Group, London – New York

[5] This points to the concept of ‘propensity’ which the late Popper has discussed in the papers [3] and [4].

[6] This concept of a ‘generator’ or an ‘inference’ reminds to the general concept of Popper and the main stream philosophy of a logical derivation concept where a ‘set of logical rules’ defines a ‘derivation concept’ which allows the ‘derivation/ inference’ of a statement s* as a ‘theorem’ from an assumed set of statements S assumed to be true.

[7] The clock-based time is in the real world correlated with certain constellations of the real universe, but this — as a whole — is ‘changing’!

[8] Hessisches Statistisches Landesamt, “Die Bevölkerung der hessischen
Gemeinden am 30. Juni 2021. Fortschreibungsergebnisse Basis Zensus 09. Mai 2011″, Okt. 2021, Wiesbaden, URL: https://statistik.hessen.de/sites/statistik.hessen.de/files/AI2_AII_AIII_AV_21-1hj.pdf

[9] Method of the forward projection of the statistical office of the State of Hessen: “Bevölkerung: Die Bevölkerungszahlen sind Fortschreibungsergebnisse, die auf den bei der Zensuszählung 2011
ermittelten Bevölkerungszahlen basieren. Durch Auswertung von elektronisch übermittelten Daten für Geburten und Sterbefälle durch die Standesämter, sowie der Zu- und Fortzüge der Meldebehörden, werden diese nach einer bundeseinheitlichen Fortschreibungsmethode festgestellt. Die Zuordnung der Personen zur Bevölkerung einer Gemeinde erfolgt nach dem Hauptwohnungsprinzip (Bevölkerung am Ort der alleinigen oder der Hauptwohnung).”([8:p.2]

[10] Statistical Office state of Hessen, Next census 2022: https://statistik.hessen.de/zahlen-fakten/zensus/zensus-2022/zensus-2022-kurz-erklaert

STARTING WITH PYTHON3 – The very beginning – part 9

Journal: uffmm.org,
ISSN 2567-6458, July 24-25, 2019
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email:gerd@doeben-henisch.de

CONTEXT

This is the next step in the python3 programming project. The overall context is still the python Co-Learning project.

SUBJECT

In this file you will see a first encounter between the AAI paradigm (described in the theory part of this uffmm blog) and some applications of the python programming language. A simple virtual world with objects and actors can become activated with a free selectable size, amount of objects and amount of actors. In later post lots of experiments with this virtual world will be described as well as many extensions.

SOURCE CODE
Main file: vw4.py

The main file ‘vw4.py’ describes the start of a virtual world and then allows a loop to run this world n-many times.

Import file: vwmanager.py

The main file ‘vw4.py’ is using many functions to enable the process. All these functions are collected in the file ‘vwmanager.py’. This file will automatically be loaded during run time of the program vw4.py.

COMMENTS

comment-vw4

DEMO

TEST RUN AUG 19, 2919, 12:56h

gerd@Doeben-Henisch:~/code$ python3 vw4.py
Amount of information: 1 is maximum, 0 is minimum0
Number of columns (= equal to rows!) of 2D-grid ?4
[‘_’, ‘_’, ‘_’, ‘_’]

[‘_’, ‘_’, ‘_’, ‘_’]

[‘_’, ‘_’, ‘_’, ‘_’]

[‘_’, ‘_’, ‘_’, ‘_’]

Percentage (as integer) of obstacles in the 2D-grid?77
Percentage (as integer) of Food Objects in the 2D-grid ?44
Percentage (as integer) of Actor Objects in the 2D-grid ?15

Objects as obstacles

[0, 2, ‘O’]

[0, 3, ‘O’]

[1, 2, ‘O’]

[2, 3, ‘O’]

Objects as food

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Objects as actor

[1, 3, ‘A’, [0, 1000, 100, 500, 0]]

[3, 2, ‘A’, [1, 1000, 100, 500, 0]]

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘A’, ‘F’]

END OF PREPARATION

WORLD CYCLE STARTS

—————————————————-
Real percentage of obstacles = 25.0
Real percentage of food = 37.5
Real percentage of actors = 12.5
—————————————————-
How many CYCLES do you want?25
Singe Step = 1 or Continous = 0?1
Length of olA 2

—————————————————–

WORLD AT CYCLE = 0

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘A’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 1000, 100, 500, -1]]

[2, 1, ‘A’, [1, 1000, 100, 500, 8]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 1

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘A’]

[‘F’, ‘A’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 900, 100, 500, -1]]

[2, 1, ‘A’, [1, 900, 100, 500, 0]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 2

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘A’]

[‘F’, ‘A’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 800, 100, 500, -1]]

[1, 1, ‘A’, [1, 1300, 100, 500, 1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 500, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 3

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘A’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 700, 100, 500, -1]]

[2, 0, ‘A’, [1, 1700, 100, 500, 6]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 600, 100]]

[2, 0, ‘F’, [2, 500, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 4

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘A’]

[‘A’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 600, 100, 500, -1]]

[1, 0, ‘A’, [1, 1600, 100, 500, 1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 700, 100]]

[2, 0, ‘F’, [2, 600, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 5

[‘F’, ‘_’, ‘O’, ‘O’]

[‘A’, ‘F’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 500, 100, 500, -1]]

[1, 1, ‘A’, [1, 2000, 100, 500, 3]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 300, 100]]

[2, 0, ‘F’, [2, 700, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 6

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘A’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 400, 100, 500, -1]]

[1, 1, ‘A’, [1, 1900, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 400, 100]]

[2, 0, ‘F’, [2, 800, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 7

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘A’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 300, 100, 500, -1]]

[1, 1, ‘A’, [1, 1800, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 500, 100]]

[2, 0, ‘F’, [2, 900, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 8

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘A’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 200, 100, 500, -1]]

[1, 1, ‘A’, [1, 1700, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 600, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 2

—————————————————–

WORLD AT CYCLE = 9

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘A’, ‘O’, ‘A’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 3, ‘A’, [0, 100, 100, 500, 0]]

[1, 0, ‘A’, [1, 1600, 100, 500, 7]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 700, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 10

[‘F’, ‘_’, ‘O’, ‘O’]

[‘A’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 0, ‘A’, [1, 1500, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 800, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 11

[‘F’, ‘_’, ‘O’, ‘O’]

[‘A’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 0, ‘A’, [1, 1400, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 900, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 12

[‘F’, ‘_’, ‘O’, ‘O’]

[‘A’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 0, ‘A’, [1, 1300, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 13

[‘F’, ‘_’, ‘O’, ‘O’]

[‘A’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[2, 0, ‘A’, [1, 1700, 100, 500, 5]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 500, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 14

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘A’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 1, ‘A’, [1, 2100, 100, 500, 2]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 500, 100]]

[2, 0, ‘F’, [2, 600, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 15

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘A’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 0, ‘A’, [1, 2500, 100, 500, 8]]

[0, 0, ‘F’, [0, 500, 100]]

[1, 1, ‘F’, [1, 600, 100]]

[2, 0, ‘F’, [2, 700, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 16

[‘A’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 0, ‘A’, [1, 2400, 100, 500, -1]]

[0, 0, ‘F’, [0, 600, 100]]

[1, 1, ‘F’, [1, 700, 100]]

[2, 0, ‘F’, [2, 800, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 17

[‘A’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 0, ‘A’, [1, 2300, 100, 500, -1]]

[0, 0, ‘F’, [0, 700, 100]]

[1, 1, ‘F’, [1, 800, 100]]

[2, 0, ‘F’, [2, 900, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 18

[‘A’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 0, ‘A’, [1, 2200, 100, 500, -1]]

[0, 0, ‘F’, [0, 800, 100]]

[1, 1, ‘F’, [1, 900, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 19

[‘A’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 0, ‘A’, [1, 2100, 100, 500, -1]]

[0, 0, ‘F’, [0, 900, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 20

[‘A’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 0, ‘A’, [1, 2000, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 21

[‘A’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 0, ‘A’, [1, 1900, 100, 500, 0]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 22

[‘A’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[0, 1, ‘A’, [1, 1800, 100, 500, 3]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 1000, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 23

[‘F’, ‘A’, ‘O’, ‘O’]

[‘_’, ‘F’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 1, ‘A’, [1, 2200, 100, 500, 5]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 500, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

Length of olA 1

—————————————————–

WORLD AT CYCLE = 24

[‘F’, ‘_’, ‘O’, ‘O’]

[‘_’, ‘A’, ‘O’, ‘_’]

[‘F’, ‘_’, ‘F’, ‘O’]

[‘F’, ‘_’, ‘_’, ‘F’]

Press key c for continuation!c
EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE

Updated energy levels in olF and olA
[1, 1, ‘A’, [1, 2100, 100, 500, -1]]

[0, 0, ‘F’, [0, 1000, 100]]

[1, 1, ‘F’, [1, 600, 100]]

[2, 0, ‘F’, [2, 1000, 100]]

[2, 2, ‘F’, [3, 1000, 100]]

[3, 0, ‘F’, [4, 1000, 100]]

[3, 3, ‘F’, [5, 1000, 100]]

 

AAI-THEORY V2 – BLUEPRINT: Bottom-up

eJournal: uffmm.org,
ISSN 2567-6458, 27.February 2019
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Last change: 28.February 2019 (Several corrections)

CONTEXT

An overview to the enhanced AAI theory version 2 you can find here. In this post we talk about the special topic how to proceed in a bottom-up approach.

BOTTOM-UP: THE GENERAL BLUEPRINT

Outine of the process how to generate an AS
Figure 1: Outline of the process how to generate an AS with a bottom-up approach

As the introductory figure shows it is assumed here that there is a collection of citizens and experts which offer their individual knowledge, experiences, and skills to ‘put them on the table’ challenged by a given problem P.

This knowledge is in the beginning not structured. The first step in the direction of an actor story (AS) is to analyze the different contributions in a way which shows distinguishable elements with properties and relations. Such a set of first ‘objects’ and ‘relations’ characterizes a set of facts which define a ‘situation’ or a ‘state’ as a collection of ‘facts’. Such a situation/ state can also be understood as a first simple ‘model‘ as response to a given problem. A model is as such ‘static‘; it describes what ‘is’ at a certain point of ‘time’.

In a next step the group has to identify possible ‘changes‘ which can be associated with at least one fact. There can be many possible changes which eventually  need different durations to come into effect. These effects can happen  as ‘exclusive alternatives’ or in ‘parallel’. Apply the possible changes to a  situation  generates   ‘successors’ to the actual situation. A sequence of situations generated by applied changes is  usually called a ‘simulation‘.

If one allows the interaction between real actors with a simulation by associating  a real actor to one of the actors ‘inside the simulation’ one is turning the simulation into an ‘interactive simulation‘ which represents basically a ‘computer game‘ (short: ‘egame‘).

One can use interactive simulations e.g. to (i) learn about the dynamics of a model, to (ii) test the assumptions of a model, to (iii) test the knowledge and skills of the real actors.

Making new experiences with a  simulation allows a continuous improvement of the model and its change rules.

Additionally one can include more citizens and experts into this process and one can use available knowledge from databases and libraries.

EPISTEMOLOGY OF CONCEPTS

Epistemology of concepts used in an AAI Analysis rprocess
Fig.2: Epistemology of concepts used in an AAI Analysis process

As outlined in the preceding section about the blueprint of a bottom-up process there will be a heavy   usage of concepts to describe state of affairs.

The literature about this topic in philosophy as well as many scientific disciplines is overwhelmingly and therefore this small text here can only be a ‘pointer’ into a complex topic. Nevertheless I will use exactly this pointer to explore this topic further.

While the literature is mainly dealing with  more or less specific partial models, I am trying here to point out a very general framework which fits to a more genera philosophical — especially epistemological — view as well as gives respect to many results of scientific disciplines.

The main dimensions here are (i) the outside external empirical world, which connects via sensors to the (ii) internal body, especially the brain,  which works largely ‘unconscious‘, and then (iii) the ‘conscious‘ part of he brain.

The most important relationship between the ‘conscious’ and the ‘unconscious’ part of the brain is the ability of the unconscious brain to transform automatically incoming concrete sens-experiences into more   ‘abstract’ structures, which have at least three sub-dimensions: (i) different concrete material, (ii) a sub-set of extracted common properties, (iii) different sets of occurring contexts associated with the different subsets. This enables the brain to extract only a ‘few’ abstract structures (= abstract concepts)  to deal with ‘many’  concrete events. Thus the abstract concept ‘chair’ can cover many different concrete chairs which have only a few properties in common. Additionally the chairs can occur in different ‘contexts’ associating them with different ‘relations’ which can  specify  possible different ‘usages’   of  the concept ‘chair’.

Thus, if the actor perceives something which ‘matches’ some ‘known’ concept then the actor is  not only conscious about the empirical concrete phenomenon but also simultaneously about the abstract concept which will automatically be activated. ‘Immediately’ the actor ‘knows’ that this empirical something is e.g. a ‘chair’. Concrete: this concrete something is matching an abstract concept ‘chair’ which can as such cover many other concrete things too which can be as concrete somethings partially different from another concrete something.

From this follows an interesting side effect: while an actor can easily decide, whether a concrete something is there  (“it is the case, that” = “it is true”) or not (“it is not the case, that” = “it isnot true” = “it is false”), an actor can not directly decide whether an abstract concept like ‘chair’ as such is ‘true’ in the sense, that the concept ‘as a whole’ corresponds to concrete empirical occurrences. This depends from the fact that an abstract concept like ‘chair’ can match with a  nearly infinite set of possible concrete somethings which are called ‘possible instances’ of the abstract concept. But a human actor can directly   ‘check’ only a ‘few’ concrete somethings. Therefore the usage of abstract concepts like ‘chair’, ‘house’, ‘bottle’ etc. implies  inherently an ‘open set’ of ‘possible’ concrete  exemplars and therefor is the usage of such concepts necessarily a ‘hypothetical’ usage.  Because we can ‘in principle’ check the real extensions of these abstract concepts   in everyday life as long there is the ‘freedom’ to do  such checks,  we are losing the ‘truth’ of our concepts and thereby the basis for a  realistic cooperation, if this ‘freedom of checking’ is not possible.

If some incoming perception is ‘not yet known’,  because nothing given in the unconsciousness does ‘match’,  it is in a basic sens ‘new’ and the brain will automatically generate a ‘new concept’.

THE DIMENSION OF MEANING

In Figure 2 one can find two other components: the ‘meaning relation’ which maps concepts into ‘language expression’.

Language expressions inside the brain correspond to a diversity of visual, auditory, tactile or other empirical event sequences, which are in use for communicative acts.

These language expressions are usually not ‘isolated structures’ but are embedded in relations which map the expression structures to conceptual structures including  the different substantiations of the abstract concepts and the associated contexts. By these relations the expressions are attached to the conceptual structures which are called the ‘meaning‘ of the expressions and vice versa the expressions are called the ‘language articulation’ of the meaning structures.

As far as conceptual structures are related via meaning relations to language expressions then  a perception can automatically cause the ‘activation’ of the associated language expressions, which in turn can be uttered in some way. But conceptual structures   can exist  (especially with children) without an available  meaning relation.

When language expressions are used within a communicative act then  their usage can activate in all participants of the communication the ‘learned’ concepts as their intended meanings. Heaving the meaning activated in someones ‘consciousness’ this is a real phenomenon for that actor. But from the occurrence of  concepts alone does not automatically follow, that a  concept is ‘backed up’ by some ‘real matter’ in the external world. Someone can utter that it is raining, in the hearer of this utterance the intended concepts can become activated, but in the outside external world no rain is happening. In this case one has to state that the utterance of the language expressions “Look, its raining” has no counterpart in the real world, therefore we call the utterance in this case ‘false‘ or  ‘not true‘.

THE DIMENSION OF TIME

The dimension of time based on past experience and combinatoric thinking
Fig.3: The dimension of time based on past experience and combinatoric thinking

The preceding figure 2 of the conceptual space is not yet complete. There is another important dimension based on the ability of the unconscious brain to ‘store’ certain structures in a ‘timely order’ which enables an actor — under certain conditions ! — to decide whether a certain structure X occurred in the consciousness ‘before’ or ‘after’ or ‘at the same time’ as another structure Y.

Evidently the unconscious brain is able do exactly this:  (i) it can arrange the different structures under certain conditions in a ‘timely order’;  (ii)  it can detect ‘differences‘ between timely succeeding structures;  the brain (iii) can conceptualize these changes as ‘change concepts‘ (‘rules of change’), and it can  can classify different kinds of change like ‘deterministic’, ‘non-deterministic’ with different kinds of probabilities, as well as ‘arbitrary’ as in the case of ‘free learning systems‘. Free learning systems are able to behave in a ‘deterministic-like manner’, but they can also change their patterns on account of internal learning and decision processes in nearly any direction.

Based on memories of conceptual structures and derived change concepts (rules of change) the unconscious brain is able to generate different kinds of ‘possible configurations’, whose quality is  depending from the degree of dependencies within the  ‘generating  criteria’: (i) no special restrictions; (ii) empirical restrictions; (iii) empirical restrictions for ‘upcoming states’ (if all drinkable water would be consumed, then one cannot plan any further with drinkable water).

 

 

 

 

 

 

 

AAI THEORY V2 –A Philosophical Framework

eJournal: uffmm.org,
ISSN 2567-6458, 22.February 2019
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Last change: 23.February 2019 (continued the text)

Last change: 24.February 2019 (extended the text)

CONTEXT

In the overview of the AAI paradigm version 2 you can find this section  dealing with the philosophical perspective of the AAI paradigm. Enjoy reading (or not, then send a comment :-)).

THE DAILY LIFE PERSPECTIVE

The perspective of Philosophy is rooted in the everyday life perspective. With our body we occur in a space with other bodies and objects; different features, properties  are associated with the objects, different kinds of relations an changes from one state to another.

From the empirical sciences we have learned to see more details of the everyday life with regard to detailed structures of matter and biological life, with regard to the long history of the actual world, with regard to many interesting dynamics within the objects, within biological systems, as part of earth, the solar system and much more.

A certain aspect of the empirical view of the world is the fact, that some biological systems called ‘homo sapiens’, which emerged only some 300.000 years ago in Africa, show a special property usually called ‘consciousness’ combined with the ability to ‘communicate by symbolic languages’.

General setting of the homo sapiens species (simplified)
Figure 1: General setting of the homo sapiens species (simplified)

As we know today the consciousness is associated with the brain, which in turn is embedded in the body, which  is further embedded in an environment.

Thus those ‘things’ about which we are ‘conscious’ are not ‘directly’ the objects and events of the surrounding real world but the ‘constructions of the brain’ based on actual external and internal sensor inputs as well as already collected ‘knowledge’. To qualify the ‘conscious things’ as ‘different’ from the assumed ‘real things’ ‘outside there’ it is common to speak of these brain-generated virtual things either as ‘qualia’ or — more often — as ‘phenomena’ which are  different to the assumed possible real things somewhere ‘out there’.

PHILOSOPHY AS FIRST PERSON VIEW

‘Philosophy’ has many facets.  One enters the scene if we are taking the insight into the general virtual character of our primary knowledge to be the primary and irreducible perspective of knowledge.  Every other more special kind of knowledge is necessarily a subspace of this primary phenomenological knowledge.

There is already from the beginning a fundamental distinction possible in the realm of conscious phenomena (PH): there are phenomena which can be ‘generated’ by the consciousness ‘itself’  — mostly called ‘by will’ — and those which are occurring and disappearing without a direct influence of the consciousness, which are in a certain basic sense ‘given’ and ‘independent’,  which are appearing  and disappearing according to ‘their own’. It is common to call these independent phenomena ’empirical phenomena’ which represent a true subset of all phenomena: PH_emp  PH. Attention: These empirical phenomena’ are still ‘phenomena’, virtual entities generated by the brain inside the brain, not directly controllable ‘by will’.

There is a further basic distinction which differentiates the empirical phenomena into those PH_emp_bdy which are controlled by some processes in the body (being tired, being hungry, having pain, …) and those PH_emp_ext which are controlled by objects and events in the environment beyond the body (light, sounds, temperature, surfaces of objects, …). Both subsets of empirical phenomena are different: PH_emp_bdy PH_emp_ext = 0. Because phenomena usually are occurring  associated with typical other phenomena there are ‘clusters’/ ‘pattern’ of phenomena which ‘represent’ possible events or states.

Modern empirical science has ‘refined’ the concept of an empirical phenomenon by introducing  ‘standard objects’ which can be used to ‘compare’ some empirical phenomenon with such an empirical standard object. Thus even when the perception of two different observers possibly differs somehow with regard to a certain empirical phenomenon, the additional comparison with an ’empirical standard object’ which is the ‘same’ for both observers, enhances the quality, improves the precision of the perception of the empirical phenomena.

From these considerations we can derive the following informal definitions:

  1. Something is ‘empirical‘ if it is the ‘real counterpart’ of a phenomenon which can be observed by other persons in my environment too.
  2. Something is ‘standardized empirical‘ if it is empirical and can additionally be associated with a before introduced empirical standard object.
  3. Something is ‘weak empirical‘ if it is the ‘real counterpart’ of a phenomenon which can potentially be observed by other persons in my body as causally correlated with the phenomenon.
  4. Something is ‘cognitive‘ if it is the counterpart of a phenomenon which is not empirical in one of the meanings (1) – (3).

It is a common task within philosophy to analyze the space of the phenomena with regard to its structure as well as to its dynamics.  Until today there exists not yet a complete accepted theory for this subject. This indicates that this seems to be some ‘hard’ task to do.

BRIDGING THE GAP BETWEEN BRAINS

As one can see in figure 1 a brain in a body is completely disconnected from the brain in another body. There is a real, deep ‘gap’ which has to be overcome if the two brains want to ‘coordinate’ their ‘planned actions’.

Luckily the emergence of homo sapiens with the new extended property of ‘consciousness’ was accompanied by another exciting property, the ability to ‘talk’. This ability enabled the creation of symbolic languages which can help two disconnected brains to have some exchange.

But ‘language’ does not consist of sounds or a ‘sequence of sounds’ only; the special power of a language is the further property that sequences of sounds can be associated with ‘something else’ which serves as the ‘meaning’ of these sounds. Thus we can use sounds to ‘talk about’ other things like objects, events, properties etc.

The single brain ‘knows’ about the relationship between some sounds and ‘something else’ because the brain is able to ‘generate relations’ between brain-structures for sounds and brain-structures for something else. These relations are some real connections in the brain. Therefore sounds can be related to ‘something  else’ or certain objects, and events, objects etc.  can become related to certain sounds. But these ‘meaning relations’ can only ‘bridge the gap’ to another brain if both brains are using the same ‘mapping’, the same ‘encoding’. This is only possible if the two brains with their bodies share a real world situation RW_S where the perceptions of the both brains are associated with the same parts of the real world between both bodies. If this is the case the perceptions P(RW_S) can become somehow ‘synchronized’ by the shared part of the real world which in turn is transformed in the brain structures P(RW_S) —> B_S which represent in the brain the stimulating aspects of the real world.  These brain structures B_S can then be associated with some sound structures B_A written as a relation  MEANING(B_S, B_A). Such a relation  realizes an encoding which can be used for communication. Communication is using sound sequences exchanged between brains via the body and the air of an environment as ‘expressions’ which can be recognized as part of a learned encoding which enables the receiving brain to identify a possible meaning candidate.

DIFFERENT MODES TO EXPRESS MEANING

Following the evolution of communication one can distinguish four important modes of expressing meaning, which will be used in this AAI paradigm.

VISUAL ENCODING

A direct way to express the internal meaning structures of a brain is to use a ‘visual code’ which represents by some kinds of drawing the visual shapes of objects in the space, some attributes of  shapes, which are common for all people who can ‘see’. Thus a picture and then a sequence of pictures like a comic or a story board can communicate simple ideas of situations, participating objects, persons and animals, showing changes in the arrangement of the shapes in the space.

Pictorial expressions representing aspects of the visual and the auditory sens modes
Figure 2: Pictorial expressions representing aspects of the visual and the auditory sens modes

Even with a simple visual code one can generate many sequences of situations which all together can ‘tell a story’. The basic elements are a presupposed ‘space’ with possible ‘objects’ in this space with different positions, sizes, relations and properties. One can even enhance these visual shapes with written expressions of  a spoken language. The sequence of the pictures represents additionally some ‘timely order’. ‘Changes’ can be encoded by ‘differences’ between consecutive pictures.

FROM SPOKEN TO WRITTEN LANGUAGE EXPRESSIONS

Later in the evolution of language, much later, the homo sapiens has learned to translate the spoken language L_s in a written format L_w using signs for parts of words or even whole words.  The possible meaning of these written expressions were no longer directly ‘visible’. The meaning was now only available for those people who had learned how these written expressions are associated with intended meanings encoded in the head of all language participants. Thus only hearing or reading a language expression would tell the reader either ‘nothing’ or some ‘possible meanings’ or a ‘definite meaning’.

A written textual version in parallel to a pictorial version
Figure 3: A written textual version in parallel to a pictorial version

If one has only the written expressions then one has to ‘know’ with which ‘meaning in the brain’ the expressions have to be associated. And what is very special with the written expressions compared to the pictorial expressions is the fact that the elements of the pictorial expressions are always very ‘concrete’ visual objects while the written expressions are ‘general’ expressions allowing many different concrete interpretations. Thus the expression ‘person’ can be used to be associated with many thousands different concrete objects; the same holds for the expression ‘road’, ‘moving’, ‘before’ and so on. Thus the written expressions are like ‘manufacturing instructions’ to search for possible meanings and configure these meanings to a ‘reasonable’ complex matter. And because written expressions are in general rather ‘abstract’/ ‘general’ which allow numerous possible concrete realizations they are very ‘economic’ because they use minimal expressions to built many complex meanings. Nevertheless the daily experience with spoken and written expressions shows that they are continuously candidates for false interpretations.

FORMAL MATHEMATICAL WRITTEN EXPRESSIONS

Besides the written expressions of everyday languages one can observe later in the history of written languages the steady development of a specialized version called ‘formal languages’ L_f with many different domains of application. Here I am  focusing   on the formal written languages which are used in mathematics as well as some pictorial elements to ‘visualize’  the intended ‘meaning’ of these formal mathematical expressions.

Properties of an acyclic directed graph with nodes (vertices) and edges (directed edges = arrows)
Fig. 4: Properties of an acyclic directed graph with nodes (vertices) and edges (directed edges = arrows)

One prominent concept in mathematics is the concept of a ‘graph’. In  the basic version there are only some ‘nodes’ (also called vertices) and some ‘edges’ connecting the nodes.  Formally one can represent these edges as ‘pairs of nodes’. If N represents the set of nodes then N x N represents the set of all pairs of these nodes.

In a more specialized version the edges are ‘directed’ (like a ‘one way road’) and also can be ‘looped back’ to a node   occurring ‘earlier’ in the graph. If such back-looping arrows occur a graph is called a ‘cyclic graph’.

Directed cyclic graph extended to represent 'states of affairs'
Fig.5: Directed cyclic graph extended to represent ‘states of affairs’

If one wants to use such a graph to describe some ‘states of affairs’ with their possible ‘changes’ one can ‘interpret’ a ‘node’ as  a state of affairs and an arrow as a change which turns one state of affairs S in a new one S’ which is minimally different to the old one.

As a state of affairs I  understand here a ‘situation’ embedded in some ‘context’ presupposing some common ‘space’. The possible ‘changes’ represented by arrows presuppose some dimension of ‘time’. Thus if a node n’  is following a node n indicated by an arrow then the state of affairs represented by the node n’ is to interpret as following the state of affairs represented in the node n with regard to the presupposed time T ‘later’, or n < n’ with ‘<‘ as a symbol for a timely ordering relation.

Example of a state of affairs with a 2-dimensional space configured as a grid with a black and a white token
Fig.6: Example of a state of affairs with a 2-dimensional space configured as a grid with a black and a white token

The space can be any kind of a space. If one assumes as an example a 2-dimensional space configured as a grid –as shown in figure 6 — with two tokens at certain positions one can introduce a language to describe the ‘facts’ which constitute the state of affairs. In this example one needs ‘names for objects’, ‘properties of objects’ as well as ‘relations between objects’. A possible finite set of facts for situation 1 could be the following:

  1. TOKEN(T1), BLACK(T1), POSITION(T1,1,1)
  2. TOKEN(T2), WHITE(T2), POSITION(T2,2,1)
  3. NEIGHBOR(T1,T2)
  4. CELL(C1), POSITION(1,2), FREE(C1)

‘T1’, ‘T2’, as well as ‘C1’ are names of objects, ‘TOKEN’, ‘BACK’ etc. are names of properties, and ‘NEIGHBOR’ is a relation between objects. This results in the equation:

S1 = {TOKEN(T1), BLACK(T1), POSITION(T1,1,1), TOKEN(T2), WHITE(T2), POSITION(T2,2,1), NEIGHBOR(T1,T2), CELL(C1), POSITION(1,2), FREE(C1)}

These facts describe the situation S1. If it is important to describe possible objects ‘external to the situation’ as important factors which can cause some changes then one can describe these objects as a set of facts  in a separated ‘context’. In this example this could be two players which can move the black and white tokens and thereby causing a change of the situation. What is the situation and what belongs to a context is somewhat arbitrary. If one describes the agriculture of some region one usually would not count the planets and the atmosphere as part of this region but one knows that e.g. the sun can severely influence the situation   in combination with the atmosphere.

Change of a state of affairs given as a state which will be enhanced by a new object
Fig.7: Change of a state of affairs given as a state which will be enhanced by a new object

Let us stay with a state of affairs with only a situation without a context. The state of affairs is     a ‘state’. In the example shown in figure 6 I assume a ‘change’ caused by the insertion of a new black token at position (2,2). Written in the language of facts L_fact we get:

  1. TOKEN(T3), BLACK(T3), POSITION(2,2), NEIGHBOR(T3,T2)

Thus the new state S2 is generated out of the old state S1 by unifying S1 with the set of new facts: S2 = S1 {TOKEN(T3), BLACK(T3), POSITION(2,2), NEIGHBOR(T3,T2)}. All the other facts of S1 are still ‘valid’. In a more general manner one can introduce a change-expression with the following format:

<S1, S2, add(S1,{TOKEN(T3), BLACK(T3), POSITION(2,2), NEIGHBOR(T3,T2)})>

This can be read as follows: The follow-up state S2 is generated out of the state S1 by adding to the state S1 the set of facts { … }.

This layout of a change expression can also be used if some facts have to be modified or removed from a state. If for instance  by some reason the white token should be removed from the situation one could write:

<S1, S2, subtract(S1,{TOKEN(T2), WHITE(T2), POSITION(2,1)})>

Another notation for this is S2 = S1 – {TOKEN(T2), WHITE(T2), POSITION(2,1)}.

The resulting state S2 would then look like:

S2 = {TOKEN(T1), BLACK(T1), POSITION(T1,1,1), CELL(C1), POSITION(1,2), FREE(C1)}

And a combination of subtraction of facts and addition of facts would read as follows:

<S1, S2, subtract(S1,{TOKEN(T2), WHITE(T2), POSITION(2,1)}, add(S1,{TOKEN(T3), BLACK(T3), POSITION(2,2)})>

This would result in the final state S2:

S2 = {TOKEN(T1), BLACK(T1), POSITION(T1,1,1), CELL(C1), POSITION(1,2), FREE(C1),TOKEN(T3), BLACK(T3), POSITION(2,2)}

These simple examples demonstrate another fact: while facts about objects and their properties are independent from each other do relational facts depend from the state of their object facts. The relation of neighborhood e.g. depends from the participating neighbors. If — as in the example above — the object token T2 disappears then the relation ‘NEIGHBOR(T1,T2)’ no longer holds. This points to a hierarchy of dependencies with the ‘basic facts’ at the ‘root’ of a situation and all the other facts ‘above’ basic facts or ‘higher’ depending from the basic facts. Thus ‘higher order’ facts should be added only for the actual state and have to be ‘re-computed’ for every follow-up state anew.

If one would specify a context for state S1 saying that there are two players and one allows for each player actions like ‘move’, ‘insert’ or ‘delete’ then one could make the change from state S1 to state S2 more precise. Assuming the following facts for the context:

  1. PLAYER(PB1), PLAYER(PW1), HAS-THE-TURN(PB1)

In that case one could enhance the change statement in the following way:

<S1, S2, PB1,insert(TOKEN(T3,2,2)),add(S1,{TOKEN(T3), BLACK(T3), POSITION(2,2)})>

This would read as follows: given state S1 the player PB1 inserts a  black token at position (2,2); this yields a new state S2.

With or without a specified context but with regard to a set of possible change statements it can be — which is the usual case — that there is more than one option what can be changed. Some of the main types of changes are the following ones:

  1. RANDOM
  2. NOT RANDOM, which can be specified as follows:
    1. With PROBABILITIES (classical, quantum probability, …)
    2. DETERMINISTIC

Furthermore, if the causing object is an actor which can adapt structurally or even learn locally then this actor can appear in some time period like a deterministic system, in different collected time periods as an ‘oscillating system’ with different behavior, or even as a random system with changing probabilities. This make the forecast of systems with adaptive and/ or learning systems rather difficult.

Another aspect results from the fact that there can be states either with one actor which can cause more than one action in parallel or a state with multiple actors which can act simultaneously. In both cases the resulting total change has eventually to be ‘filtered’ through some additional rules telling what  is ‘possible’ in a state and what not. Thus if in the example of figure 6 both player want to insert a token at position (2,2) simultaneously then either  the rules of the game would forbid such a simultaneous action or — like in a computer game — simultaneous actions are allowed but the ‘geometry of a 2-dimensional space’ would not allow that two different tokens are at the same position.

Another aspect of change is the dimension of time. If the time dimension is not explicitly specified then a change from some state S_i to a state S_j does only mark the follow up state S_j as later. There is no specific ‘metric’ of time. If instead a certain ‘clock’ is specified then all changes have to be aligned with this ‘overall clock’. Then one can specify at what ‘point of time t’ the change will begin and at what point of time t*’ the change will be ended. If there is more than one change specified then these different changes can have different timings.

THIRD PERSON VIEW

Up until now the point of view describing a state and the possible changes of states is done in the so-called 3rd-person view: what can a person perceive if it is part of a situation and is looking into the situation.  It is explicitly assumed that such a person can perceive only the ‘surface’ of objects, including all kinds of actors. Thus if a driver of a car stears his car in a certain direction than the ‘observing person’ can see what happens, but can not ‘look into’ the driver ‘why’ he is steering in this way or ‘what he is planning next’.

A 3rd-person view is assumed to be the ‘normal mode of observation’ and it is the normal mode of empirical science.

Nevertheless there are situations where one wants to ‘understand’ a bit more ‘what is going on in a system’. Thus a biologist can be  interested to understand what mechanisms ‘inside a plant’ are responsible for the growth of a plant or for some kinds of plant-disfunctions. There are similar cases for to understand the behavior of animals and men. For instance it is an interesting question what kinds of ‘processes’ are in an animal available to ‘navigate’ in the environment across distances. Even if the biologist can look ‘into the body’, even ‘into the brain’, the cells as such do not tell a sufficient story. One has to understand the ‘functions’ which are enabled by the billions of cells, these functions are complex relations associated with certain ‘structures’ and certain ‘signals’. For this it is necessary to construct an explicit formal (mathematical) model/ theory representing all the necessary signals and relations which can be used to ‘explain’ the obsrvable behavior and which ‘explains’ the behavior of the billions of cells enabling such a behavior.

In a simpler, ‘relaxed’ kind of modeling  one would not take into account the properties and behavior of the ‘real cells’ but one would limit the scope to build a formal model which suffices to explain the oservable behavior.

This kind of approach to set up models of possible ‘internal’ (as such hidden) processes of an actor can extend the 3rd-person view substantially. These models are called in this text ‘actor models (AM)’.

HIDDEN WORLD PROCESSES

In this text all reported 3rd-person observations are called ‘actor story’, independent whether they are done in a pictorial or a textual mode.

As has been pointed out such actor stories are somewhat ‘limited’ in what they can describe.

It is possible to extend such an actor story (AS)  by several actor models (AM).

An actor story defines the situations in which an actor can occur. This  includes all kinds of stimuli which can trigger the possible senses of the actor as well as all kinds of actions an actor can apply to a situation.

The actor model of such an actor has to enable the actor to handle all these assumed stimuli as well as all these actions in the expected way.

While the actor story can be checked whether it is describing a process in an empirical ‘sound’ way,  the actor models are either ‘purely theoretical’ but ‘behavioral sound’ or they are also empirically sound with regard to the body of a biological or a technological system.

A serious challenge is the occurrence of adaptiv or/ and locally learning systems. While the actor story is a finite  description of possible states and changes, adaptiv or/ and locally learning systeme can change their behavior while ‘living’ in the actor story. These changes in the behavior can not completely be ‘foreseen’!

COGNITIVE EXPERT PROCESSES

According to the preceding considerations a homo sapiens as a biological system has besides many properties at least a consciousness and the ability to talk and by this to communicate with symbolic languages.

Looking to basic modes of an actor story (AS) one can infer some basic concepts inherently present in the communication.

Without having an explicit model of the internal processes in a homo sapiens system one can infer some basic properties from the communicative acts:

  1. Speaker and hearer presuppose a space within which objects with properties can occur.
  2. Changes can happen which presuppose some timely ordering.
  3. There is a disctinction between concrete things and abstract concepts which correspond to many concrete things.
  4. There is an implicit hierarchy of concepts starting with concrete objects at the ‘root level’ given as occurence in a concrete situation. Other concepts of ‘higher levels’ refer to concepts of lower levels.
  5. There are different kinds of relations between objects on different conceptual levels.
  6. The usage of language expressions presupposes structures which can be associated with the expressions as their ‘meanings’. The mapping between expressions and their meaning has to be learned by each actor separately, but in cooperation with all the other actors, with which the actor wants to share his meanings.
  7. It is assume that all the processes which enable the generation of concepts, concept hierarchies, relations, meaning relations etc. are unconscious! In the consciousness one can  use parts of the unconscious structures and processes under strictly limited conditions.
  8. To ‘learn’ dedicated matters and to be ‘critical’ about the quality of what one is learnig requires some disciplin, some learning methods, and a ‘learning-friendly’ environment. There is no guaranteed method of success.
  9. There are lots of unconscious processes which can influence understanding, learning, planning, decisions etc. and which until today are not yet sufficiently cleared up.