[ieee 2010 11th international symposium on computational intelligence and informatics (cinti) -...

Computational Intelligence: An Excellent Way to Theorising in Social Sciences

Ladislav Andrášik Slovak university of technology Bratislava

[email protected]

Abstract - The creation of theories in the class of social sciences by the CI assistance is considered. The author asserts that there are at least two possible approaches to spread out some social theories by the assistance of CI. The first is so called fabula like approach to evolving theory. The second one is sujet akin. Both we can understand as metaphor for divergent forms of narrative construction of social theory. Those two possible approaches narrowly correspond with two methods of building computational models for theories: the first is method of creation model from bottom to up and the opposite one – from up to down. Because the most of social phenomena are discrete nature there is emerging the needs to apply advance and so, of course, difficult topological methods. In those circumstances are coming the alternative helps from CI assistance. The author also maintains that majority of social phenomena have population-like-evolving character. The other separation of social theories is coming apart quantitative (and/or statistical, econometrical) approaches against qualitative one. That spirit of possible social theories is in narrow correlation with fabula-sujet like approaches. The present paper focuses some examples of partial theories of social sciences building by the aid of CI products. The author emphasizes focus on qualitative social theories.

Keywords - Abstracted mental model, ANN (CINN), CI built phenotypes, CI built theories, Competition, Complex phenomena, Creative destruction in social sciences, fabula versus sujet like creation, interactive theory building environment built in PC software, local-global stability, mapping of genotypes and phenotypes, MAS, GA (EA), mathematical genotypes, Mode “3”, Racketeering, Tunneling, science phenotype

I. INTRODUCTION In contemporary social science and partial socio-

economic theories the need for deeper exact understandings of behaviors in developments is increasing. The era of simple social theories without serious mathematical base are outdone long ago. But the suitable using of mathematical approaches and tools is not easy job first of all in the case of very complex social and economic phenomena in the era of global knowledge based society. On the other hand the character of complex phenomena is so deep, that results of “clean” and clear mathematics is too difficult for imaginations in the mind of current scholars in social theories. In this situation are arising authentic and very needs for new excellent and efficient at those jobs methods and tools for investigation. We must acknowledge that there is several application of CI to modelling fables on social sciences at present. More advanced among others there are some applications in the

class of economic sciences. Namely it is achieved success in modelling autonomous agents in agent-based computational models in economic and finance, and similar advances was achieved with application of ANN1 to those fields of science. From the point of view of author of present paper and also based of his opinions the more useful are those applications allowing lead dialogs with computational subjects like softbots living in appropriate software and/or in advanced virtual laboratories.

In upper described situation the creation of theories in the class of social sciences by the CI assistance is considered by author. So he asserts that there are at least two possible approaches to spread out some social theories by the assistance of CI. The first is so called fabula like approach to evolving theory. The second one is sujet like. Fabula and sujet2, or fabula against sujet is one of the important methodological questions of theorizing in the field of social sciences. Both we can understand as divergent forms of narrative construction of social theory. Those two possible approaches narrowly correspond with two methods of building computational models for theories: the first is method of creation model from bottom to up and the opposite one – from up to down. Because the most of social phenomena are discrete nature there is emerging the needs to apply advance and so, of course, difficult topological methods. In those circumstances are coming the alternative helps from CI assistance. The author also maintains that majority of social phenomena have population-like-evolving character. The other separation of social theories is coming apart quantitative (and/or statistical, econometrical) approaches against qualitative one. That spirit of possible social theories is in narrow correlation with fabula-sujet like approaches. The present paper focuses some examples of partial theories of social sciences building by the aid of CI products. The author emphasizes focus on qualitative social theories.

In high level of generality meaning the qualitative reasoning (QR) field has developed various representation and reasoning methods for the modelling with incomplete information or incomplete knowledge. But this is only one of wide variety of possible interpretation of qualitative reasoning. Essentially, in the process of creation and building social theories one can accept this approach. So

1 Instead of Artificial attribute in abbreviation ANN we prefer of Computational Intelligence one (CINN=By CI created Neural Network). 2 In theory of writing literary stories (and/or tales, etc.) the sujet is an employment of narrative on evolving process to some end and fabula is the order of re-telling already existing events.

CINTI 2010 • 11th IEEE International Symposium on Computational Intelligence and Informatics • 18–20 November, 2010 • Budapest, Hungary

978-1-4244-9280-0/10/$26.00 ©2010 IEEE- 193 -

{1 2: ´ 1 ( 1) ( 1) .DT x x x b x⎡ ⎤= − − + −⎣ ⎦

by this approach, it is clear that while most uncertain reasoning approaches describe uncertain or imprecisely known information as probability distribution functions, qualitative reasoning bases its model specification on qualitative descriptions that are derived from known qualitative system properties. Problems are formulated as sets of qualitative constraints and their analysis is performed by applying a qualitative calculus. In this paper we uses and presents a general, unifying theory of the various existing qualitative reasoning systems that includes, as special cases, reasoning methods that use representations of qualitative differential equations and qualitative difference equations. The last one gain the form of topological maps, because the investigation of qualitative shape of socio-evolution is need looking for impact of singular point of evolution (that is in iteration running) on possible emergences of new qualitative shapes of the investigated entity. Based on set theory, our QR framework describes fundamental concepts such as qualitative models and solutions, and relates them to the quantitative analogues of its underlying quantitative reference system. Our motivation arises from the types of models found in the social sciences and namely in economics and management sciences. Thus we emphasize the significance of discrete, dynamic models and optimization models in the business management and economics fields, both of which have received less attention in current QR research. Finally, we can extend our theoretical framework to include an approach to qualitative optimization. So those approaches are bringing social theories by abstractions upon by human subject made reality. Currently such imagination and simulation product are marked by attribute “artificial”. By our opinion it is not accurate altogether. For example economic scholars around Professor Charlotte Bruun are currently using the term “Artificial economics” but their products are achieved by using CI methods and products. As such approach is narrower then sense of term “artificial”. On the other hand one can successfully hesitate if it is fact “Economics”, that is the branch of social science, or “Economy” as some complex entity. In the symposium “Artificial Economics 2006”, namely in Preface to Proceedings [3], pp. v-vi is quoted: “Artificial economics is a methodological approach rather than a paradigmatic approach”. But Economics is the branch of science not some “methodological approach”. In fact the contributors of that Symposium are using several methods and tools belonging to the sphere of CI such as MAS (that is distributed CI products), Evolutionary algorithms, Evolutionary programming, and Genetic algorithm, CINN, Knowledge system and others. So we can rather have in mind real intellectual products of scholars achieved by the aid and/or assistance of various methods, product and tools of CI. By the way, one further product in that series [9] is coming nearer to authors of actual paper perceiving. For example the contribution of Russian scholars V. Romanov at al., are using in their paper the term “Agent-based Computational Economy” [9], p. 191. In this sense, because this product is achieved by human-subjects by using CI we can conditionally having in mind that this is “Artificial economy”, but not “Artificial economics”. Similar misunderstanding may arise with abbreviation ANN, and with several other economic theories using the attribute “Artificial”. The science and/or theory are among other the result of creative activities of several scholars. If that result (-s) is achieved by the

assistance or aids of CI it can’t be identified wholly with something which is in some sense “artificial”. So that entity is still remains man made creation similarly as that one achieved without help of CI. The statue remain the result of sculptor creative activities without regard what tools he was used. However the better is the tool the better can be the realized statue, and the sculptor work can be more effective too. Basically, the science as a whole is the product of mankind as such. So in this sense the totality of sciences may be attributed with term “Artificial”. This problem is very similar to several misunderstandings connected with AI and/or CI. There is natural intelligence of authentic human being. But there are also man made intelligence imputed to hardware and software. This is also the form of natural intelligence derivate and performed by ICT. And at last there are another intelligence spontaneously emerging in man made virtual environment as a result of evolutionary learning independently of human constructor. In the case of partial theory building this is something as sujet-mod approaches: 1. made by authentic human subject, 2. partially emerging in computation3 process, for example in MAS laboratory. But from the point of view of user of CI products, and tools for example also such as may be simple virtual laboratory such entity may play the role of “dialogue partner”, that is not human but intelligent partner because that “alien” is gifted by ability to answer relatively difficult questions asked with him. In subsequent parts of this paper the author will exhibit some very simple issues belonging to meant field. He emphasizes that one thing is the investigation of real society and wholly other one is the investigation of virtual entity. The differences are not only in objects of investigation but in the subject of analysis and in possible usable methods and tools. In other word the approaches are correct only if a scholar respects all nuances of the deep differences between objects (real entity versus virtual entity) and also the specific differences between two subjects formulated for investigation upon these objects.

II. RE-TELLING QUALITATIVE EVENTS IN ABSTRACT DISCRETE STORY ASSISTED BY CI DEVICES AND TOOLS If we have forehand done formalized composition part

of some social theories it is natural need to look after possible events emerging in some interval of story involved it in. Let us consider relatively simple derivate of some abstract social entity evolution in 1D form

(1)

This map we can perceive as formalized genotype. This one can be unfolded to phenotype in mathematic form and in form of running in virtual laboratory creature. Without preliminary mathematical analysis that map we are directly step to looking after qualitative events possibly emerging in the tale. It is easy and exemplary doing this task in virtual laboratory built in environment iDmc4 3 By the way the proficient computational modeling in social science began at least as far back as the nineteen fifties in works of Herbert Simon [16]. 4 The authors of that device are M. Lines and A. Medio [10]. It is in the Internet and the downloading is free.

L. Andrášik • Computational Intelligence: An Excellent Way to Theorising in Social Sciences

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--@@ name = “Sociomodel” description = “See form(1) in Andrasik paper: Budapest 2010, 11th Symposium“ type = “D” parameters = {“a”, “b”} variables = {“x”} function f(a, b, x) x1 = x*(1-a*(x-1)+b*(x^2-2*x+1)) return x1 end function Jf(a, b, x) return 1-2*a*x-1+3*b*x^2-4*b*x+b end

In upper laboratory we can by variety of simulation routine look for possible emergence of qualitative events by using algorithm (or routine) “Cobweb animation” (see snapshot of Fig. 1) and by more detail routine “Bifurcation”, for instance bifurcation portrait of one parameter against variable, one parameter against other one (Figs. 2 and 4). Laboratory of abstract “Sociomodel” is the some metaphoric partner to dialog. It can be

interpreted as model of dynamic contradiction between growth part of natural resources and the growth part of their consumption. The change of balance done by relation between parameter a to parameter b show the dynamics possibly going to qualitative change of this entity evolution. The investigator can ask the question “What is happen when I am changing single parameter, or both and when I am changing the starting point of variable x0. We can already by intuition see that the great difference between those values brings strange dynamic behavior of the model. Period doubling bifurcation in the early interval of evolution can be achieved with iDmc routines “Cobweb animation”, “Bifurcation” (single and double parameters), and partly by routine “Time plot”. In addition we can see that there are also 3-period, 5-period, 6-period and chaotic events. The investigator can also achieve graph of Lyapunov exponent for judge on stability conditions, Fig. 3. These five products as partial phenotypes are creating the entirety of CI body of phenotype. By leading dialog via these routines to scholar can gain clear imagine of the matter and use it for as analogue for imagination on real society and for creation partial theories. In every case this is a little better method than sheer scribble to the gravel.

Fig. 1

Fig. 2


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22

':

'D x y

Ty a bx x xy

=⎧⎨ = + + −⎩

Fig. 3

Fig. 4

Fig. 5

III. 3 HELPING IMAGINATION ON 2D ENTITIES BY THE ASSISTANCE OF SIMULATION IN CI ENVIRONMENT

The imagination on 2D dynamical systems is more difficult then on 1D one, above all when it is discrete (that is when it is topological map). The potency of such model to generate strange qualitative behaviour is extraordinary high. The imagination on meant complex behaviour is really difficult and it is not great revelation that in conventional economic literature one can find a lot of false interpretation on possible behaviour of various

economic entities because of existing problems with imagination abilities of scholars. Let us now demonstrate the great difference between behaviour of continues dynamical systems and discrete one. For this purpose first we are using the famous Bogdanov-Takens bifurcation. The formalized genotype (germ of iteration) is for continuous germ

(2a) and for discrete one is


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2

y

a bx x xy

xy

=

= + + −

i

i · (2b)

The laboratory in iDmc for (2a) is as follow --@@ name = "Takens-Bogdanov Conti" description = "See Andrasik text …" type = "C"

Fig. 6 parameters = {"a", "b", "c"} variables = {"x", "y"} function f(a, b, c, x, y) x1 = y y1 = a + b*x + x^2 - c*x*y return x1, y1 end function Jf(a, b, c, x, y) return 0, 1, b + 2*x - c, - c end

In the snapshot of Fig. 6 we can see that trajectories

starting from singular points situated in the area of third quadrant are winding on attractive focus (The origin of this coordinate system is the saddle point). The trajectories originated in the other three quadrants are repulsive and going away to +∞, with the exception of four main branches of saddle point as it can see in snapshot of Fig. 7. In this more clear we can see the possible emergence of closed invariant curves, so we can imagine on homo- and/or hetero-clinic tangles. Parabola in left snapshot from simulation in Excel is the curve of

saddle-node bifurcation. Its branch in first quadrant has repulsive node half of saddle and in forth quadrant the situation is opposite, the node half of the saddle is attractive (left snapshot of Fig. 8). In Fig. 9 there are little different in possibility for watching situations than in Figs. 6 and 7. We see that one of two attractive branch of the saddle is apparently repulsive focus but it is sham. In fact this shape of branch creates one of infinitesimal boundary for inner attractive focus. This complicate situation is intuitively unforeseeable and worst for understanding is that mathematical procedures respectively facilitating that are moreover difficult.

Fig. 7


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Fig. 8

Fig. 9

Fig. 10


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Fig. 11

Fig. 12

The shapes in Figs. 10-12 shows that bifurcation of continuous Bogdanov-Takens objects simulated in virtual laboratories can bring emergencies of very different qualitative events. This facts and first of all the possibility to go ahead dialogs with running process is very useful for understanding less complex behaviours of entities studied in social and cognitive sciences. It is clearly understandable that these upper exhibited continuous entity is perfectly fit for analogizing phenomena in physics, namely in electricity and first of all for analyzing possible strange events in real power system, for example such events as collapse of voltage. But it is not so evident that models based on continual Bogdanov-Takens bifurcation is usable also for studying strange behaviours in biology, ecology, cognitive sciences and social sciences too. However the more promising using is its discrete variety. Bifurcation Bogdanov-Takens as topological maps is the topic of subsequent demonstration. In snapshot of Fig. 13 we can see the situation when from unstable fixed point (focus) are evolving the system to for saddles and further the state point reach for stable nodes and rotate on them (jumping from one point to subsequent an so on. Those periodic points are stable in their loci. In Fig. 14 there is the basin of attractor with four saddles and nodes created in routine “Cycles”. In that snapshot one can clearly see the partial basins of four attractive nodes. In Fig. 15 there is result of another simulation. In basin of attraction there are fourteen saddles and nodes also gained by using the iDmc routine “Cycles”. The body of phenotype in this case is richer then the former 1D one.

Very special qualitative events emerged in snapshot of Fig. 16. We can see that in special circumstances, that is when the parameters have appropriate values there are evolving partial closed invariant curve, saddles and attractive curves in interiors of those curves. But this is only 2D entity and what complicate behaviour can emerging in them! What strange can be the behaviour when the object is 3D and high n-D what is situation in social reality apparent? With re-telling former primordial theories by the assistance of relative simple virtual laboratories scholars can at least reveal the former naivety an maybe more than that. For successful qualitative reasoning in social sciences maybe to evolving on the dialog with virtual laboratories is more important than resulting phenotype alone. In this connection the process of dialog one can regard as higher for of scribbling to the sand, or on paper or on blackboard. Re-telling or reconstructing the primary (primordial, original) genotypic germ by the devices and method of CI have et least two great gains for scientific reasoning in creation theory: the first achieving is from constructivist activation of deeper structure of scientist reasoning not only of vigilant mind on sense of right and wrong but also (possible) influence of the second phase of future dream. (sequences of following sleeps) and the second one is the evolving dialog alone. By the aid of CI the primordial germ must not be only in abrupt mathematical form but can put on clouds block and also principal diagrams. This is the theme of the next section.


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Fig. 13

Fig. 14

Fig. 15


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,C BQΔ=

Fig. 16

IV. THE CASE OF NON-RENEWABLE RESOURCES: COMPETITIVE SCARCITY SIMPLE INSPECTION MODEL

In social, psychological, ethological and economic interactions there are several opportunities for arising conflicts. For understanding character of such events and possible way for their resolution need very sophisticated insight into deep layers of those process. Let us now manipulate with relative simple model of competitive scarcity constructed in the STELLA environment. That model was suggested by M. Ruth and B. Hannon in [17, p. 171]. For the special purposes of this paper it is very important the easy possibility to construct block and principle diagrams of such complex process as conflict resolution against diminishing resources. This task has also akin to fabula character. Actually it is again the process of re-telling in advance existing germ. Its mathematical formula for maximisation profit value is as follows

∫∫ −− −==T tIT tI dteCQPdteCVPCPVP0

*

0

* .*)*(* (3)

The symbols and abbreviations in (3) are explicated as follow: CPVP (Cumulative Present Value of Profits), T (end of continuous time horizon), CVP (Current Value of Profits), Q (output as main control variable for maximisation profit), P (the price of crude resource in period t), C (the cost of extracting crude resource), e-It (discounting value by interest rate in time t). The maximisation problem (3) can be solved by using Hamiltonian mathematical procedures. For this purposes, or in more precise formulation for fulfilling building block of the schema in fig. by principles of behaviours we need to decompose entire task, that is

a) the cost of extraction is (linear function) (4) where B and Δ are external constant.

b) restriction on extraction summary quantity of resource in whole periods in interval of extraction <t=0;t=T >

0( 0) .

TY t Qdt= ≥ ∫ (5)

c) because the resource is non-renewable it must be stating that

0, and ,YQ Qt

∂≥ = −∂

(6)

because any other extractor isn’t assumed. d) Hamiltonian function is

[ ] .ItH PQ C e Qλ−= − (7)

In (7) the subtraction [ ]PQ C− is CVP at some period and is discounted at the interest rate I to yield the PVP (Present Value of Profits) in that period. The term λQ reflects the retribution (and/or tax) for by user reducing supply of resources by amount Q.

e) partial derivative of Hamiltonian relative to control variable Q is given by

0,ItH CP eQ Q

λ−⎡ ⎤∂ ∂= − − =⎢ ⎥∂ ∂⎣ ⎦ (8)

which is the condition of optimal extraction process and the way H is affected by a change in the amount of not extracted resource Y

,HQ t

λ∂ ∂− =∂ ∂

(9)

but since H is not a function of Y the value of

is 0.tλ∂ =

∂

f) on the other hand the equation (8) (because

,C MCQ

⎡ ⎤∂ =⎢ ⎥∂⎣ ⎦ that is Marginal Cost) yields

[ ] .ItP MC eλ −= − (10) g) the cumulative changes of price P(t) we can

also recognize as stock changing in time so ( ) ( ) ( ) with ( ) .P t P t dt P DT P I P MC MC= − + Δ Δ = − + Δ

(11) The above knowledge and skill of social sciences and

several others which we are omitted for saving the place are indispensable for construction of virtual laboratory first block schema and after drawing it to fulfil the building blocks Figs. 17 and 18.


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Fig. 17 Fig. 18

When the scholar are constructing the block diagram and fulfilling its building block to be transforming it to principals diagram he need nothing know on the computing program realising the transformation process phenotype from genotype (3). But he must deeply know how to transform his professional social science thinking, imagination and ideas to block and principle diagram (schema), shortly he must be generally skilled for drawing schemas in STELLA environment, or another similar software for example Simulink in MATLAB. The process running in PC in that sense is for him indifferent because he at least subconsciously perceive PC as some creative body enabling dialog with his intelligent partner hidden in his own virtual laboratory made in STELLA. The entire process may have four stages: 1. learning of primordial

(reached by conventional methods, or in ad hoc imagination or by using sujet method assisted by CI), and inclusive of appropriate mathematical knowledge and skill, 2. learning STELLA environment and their routines, gaining skill for using it, 3. creating virtual laboratory for case by name, 4. realising experiments and by obtained qualitative events and shapes, going to process of building theory and/or of recovering the former one again in higher level of understanding the matter. On part of primordial knowledge about competitive scarcity concerning the relations between quantities in one side and the prices and marginal costs on the other one is represented in diagram of Fig. 19. One result of simulation in years (in iteration steps) is in the snapshot of Fig. 20. It is clearly evident that the evolving to optimal result of solving that task can be very confused.

Fig. 19

B

C

CVP

DELTA

N

DELTA MC

DELTA P

Q

I

MC

PVP CPVP

P

Y


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Fig. 20

V. DISCUSSIONS AND SOME CONCLUSIONS

Faust: “…Two souls, alas! are lodg`d within my breast, Which struggle there for undivided reign…”

(J. W. von Goethe, Tragedy of Faust)

There was a lot of popular nonsense talked (and at present are telling too) about social theories, and especially about theories of social evolution. But maybe more nonsense is produced in interior of the social sciences alone. So we must challenge to problem: “What is truth and what is sham and/or deception in the concrete social theory?”. When is social theory really science and when is only pseudoscience? That is really the question for social theories such question as asked William Shakespeare by mouth of Hamlet: “To be or not to be…?”. The solving supplied by sir Karl Popper [14] is following statement: “…the criterion of the scientific status of a theory is its falsifiability, or refutability, or testability.”. For us such genuine device for falsification of mathematical forms of such theory is the running of virtual experiments with assistance of CI. That falsified germ is the phenotype that is prepared for comparative studies against former theory and against objective social reality.

We must unfortunately make a clean breast that the social scientists haven’t such good opportunities, a resourceful devices and a tools for verifying correctness of their statements as have scholars in natural and technical sciences. So they are referred to intuition more than natural scientists. They can’t exercise experiment in sensu stricto but only in virtual environment. On the other hand, against above written statement we must agree with fundamental methodological issue that some sort of empirical test is the primary criterion for the evaluation of social theories. We must say this even though in practice empirical tests of social theories are very complicated for well known reasons and often do not result in definite conclusions. However the primary purpose of this paper wasn’t to dealing with empirical test methodology. We upon that are presuming that social theories are objectively true or false and that the task of the social theorist is to try to determine which, in spite of the difficulties and perhaps even the impossibility of this task

in some cases. But inquiry this problem in his entirety is not our job in this paper.

In common sense the intelligence is the product of spontaneous evolution in populations of some species of living beings if not in entire living world one. Generally reasoning in very high level of abstraction may be alternatively going to the end that CI is very similar to naturally evolved intelligence because they are also spontaneously emerging but in environment made by CI professionals. Based on our opinions the position of “fabular” scholar from the field of social sciences having to use some products, devices, tools and methods from the supply of ICT, applied informatics and CI is completely indifferent to the level of advances in those professional field. For them they are very attractive assistant every such devices. The problems are arising with lack of appropriate knowledge and skill needed for efficient using them. When they are using fabula approach his situation is a little easier, because they can work with preliminary existing knowledge and can lean against their professional skill. Such situation are setting in when they want and/or are forced to use sujet akin method, that is to building the body of having in mind concrete theory from bottom to up. In the case of “fabular” methods the purpose to doing so is, among others, the deeper understanding the character of the inner content and behaviour of object and subject of conventional theory and in some case also giving some surplus to that one, by the assistance of CI. As example we can utilize the upper problem of optimisation of scarce resource extraction. The founder of that part of economic theory was H. Hotelling [7]. Similarly we can argue with several conventional economic theories those their authors converted to form of mathematical relations (formulas). The author was referred in his paper [18] on several such cases, for example those of theories of duopoly originally founded by A. A. Cournot [4] and on their reconstruction to laboratory form and re-telling done by A. Agliari [1], A. Matsumoto[12], T. Puu [15], [16], he also retold the abstract theory of monopoly. Other original theory cyclical economic growth founded by N. Kaldor [8] was retold by similar mode by A. Agliari and her co-workers [2], also by R. Herrmann [6] and by H-W. Lorenz, [11], and are retold by others too. The author of this paper retold in past 30 years more then hundred of similar theories some of them is quoted in Bibliography of [19].


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Only for illustration we presented two snapshots upon the theme duopoly achieved very simply from Excel and

iDmc Figs. 21 and 22. The progress of social entities are going in discrete steps.

Fig. 21

Fig. 22 To an action answers some reaction similarly as in

biological and ecological systems and/or in the theory of game founded by in Budapest born J. Von Neumann [22]. Not only that. The behaviour of some 2D, 3D and nD social communities in the period after 1989 in the former so-called communist countries are very similar to the behaviour of ecological (1…nD) system, for example

system of predator-prey (racketeering), 2D competition, 2D cooperation, 2D parasitism, and/or parasitoidism (tunnelling) and several similar systems. In Fig. 23 are shown the result of simulation of meant above ecological situation in a society. The typical triangular forms of the social dynamics are simulated with result in Fig. 24.


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Fig. 23

Fig. 24

Several of such system we can better understand in qualitative level by the assistance of CI devices and methods. This is very distinct away from natural and technical sciences. For theorising and learning in conventional scientific disciplines play important and beneficiary role the possibility to do experiments in real laboratories. Unfortunately in several branches of science such as social and cognitive one this resourceful approach is considerably constrained and in some one there are completely unworkable. But coming ICT, applied informatics and CI in the scene the substance of that benefit isn’t lost. The opposite is right. In that new environment not only experimentation in virtual laboratory is possible but scholars and student can to build interactive virtual scenes and or theatres with built in virtual laboratories and interactively use it for deeper permeating into problems. Advanced products and services of ICT, applied informatics and mainly CI are plays decisive role in those processes. But this is only the early stage of that fairy-tail. The more advanced are creating virtual entities for building social theories from bottom to up. The first approaches in these fields was for example entities achieved by cellular automata, by percolation theories, by Petri nets, by genetic and evolutionary algorithms, and mainly by appropriate multi-agent entities (populations). In these connections we can focuses of attention on such communities as evolving such product as computational and/or artificial economics with scholars around Ch. Bruuns [3], and LiCalzi [9], multi-agent economic simulation evolved by scientist in the

community around S. Moss [13], and the group of L. Tesfatsion [21] evolving the field of Agent-Based Computational Economics, an d scholars working in the field of ANN [20] and others inclusive coming in products of mutual integrative cooperation of social and CI scientist and pragmatic professionals from the field of informatics engineering as a future.

But the author’s goal isn’t in this paper such high level of aspirations nonetheless already without that the paper is too long. The purpose of this paper was to demonstrate that already very simple and so for potential users easy devices made by the aid of CI can efficiently help in building, writing, communicating, and reading, learning and understanding complex social theories, composed to the whole in the form of interactive virtual theatres. Among such theories may be theories from various social and cognitive scientific disciplines (sociology, psychology, ethology and various branches of economic science. On the other hand that approach can crucially help also in theorising and learning in branches of science in which experimentation in real laboratories are natural everyday custom. Our several years’ opinion is shows that already very simple devices from the side of informatics and ICT can throws new light to old maybe in most cases very deceptive beliefs on fulfilled needs of scientific character of social theories, if not on mistaken fait on correctness of conventional theories. We can argue that assistance of CI in social sciences is akin to J. Schumpeter’s creative destructions in technology [23].


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Table 1 Chronograph of three theories from Ralph Herman Abraham usable in social science theorising

The Computational Qualitative Social Sciences (CQSS) is never ended intangible entity parallel living in the authentic subjects consciences creating multilayer net united also by nets in Internet and/or other devices and methods like videoconferences etc., that is community which are furnished not only with vital human subjects but with living in CI environment population of homunculus’s like softbot’s etc. With the end of this paper we are obligate to noted that exact qualitative reasoning in social sciences are inconceivable without excellent pioneer works of mathematicians recorded in Tab. 1.

ACKNOWLEDGMENT In this paper was used some result of research granted

by VEGA 1/0877/08.

REFERENCES [1] Agliari, A., Homoclinic connections and subcritical Neimark

bifurcation in a duopoly model with adaptively adjusted productions, Chaos, Solitons and Fractals, 29, 2006, pp. 739–755, http://www.elsevier.com/locate/chaos

[2] Agliari, A., Dieci, R., Gardini, L., Homoclinic tangles in a Kaldor-like business cycle model, Journal of Economic Behavior & Organization, Vol. 62, 2007, pp. 324–347, see also: http://www.elsevier.com /locate/econbase

[3] Bruun, Ch., eds., Advances in Artificial Economics (The Economy as a Complex Dynamic System), Springer, Lecture notes in Economics and mathematical systems, No. 584, 2006.

[4] Cournot, A., Récherces sur les principes mathématiques de la théorie des richesses, Paris, 1838

[5] Fundinger, D., Lindström, T., Osipenko, G., Applied Mathematics and Computation, Vol.184, 2007, pp. 429-444, see also: http://www.elsevier.com /locate/amc

[6] Herrmann, R., Stability and Chaos in a Kaldor-type Model, DP 22, Department of Economics, University of Göttingen, 1985

[7] Hotelling, H. C., The Economics of Exhaustible Resources, Journal of Political Economy, vol. 39, 1931

[8] Kaldor, N., A Model of the Trade Cycle, Economic Journal, vol. 50, pp. 78-92

[9] LiCalzi, M., eds., Advances in Artificial Economics (Computation and Agent-Based Models), Springer, Lecture notes in Economics and mathematical systems, No. 645, 2010.

[10] Lines, M., Nonlinear Dynamics: Computer Exercises, in: Lines, M., Medio, A., Nonlinear Dynamics: A Primer, Cambridge University Press, 2001, see also: http://www.dss.uniud.it/nolinear

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