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Autor
Szuba Tadeusz (University of Science and Technology, Cracow, Poland), Szydło Stanisław (University of Science and Technology, Cracow, Poland), Skrzyński Paweł (University of Science and Technology, Cracow, Poland)
Tytuł
Computational Model of Collective Intelligence for Meta-level Analysis and Prediction of Free or Quasi-free Market Economy
Źródło
Decision Making in Manufacturing and Services, 2012, vol. 6, nr 1/2, s. 41-51, bibliogr. 8 poz.
Słowa kluczowe
Zachowania społeczne, Inteligencja, Modele symulacyjne
Social behaviour, Intelligence, Simulation models
Uwagi
summ.
Abstrakt
This paper encourages the use of a computational model of Collective Intelligence as a major (meta-level) tool to analyze and predict behavior of socio-economical systems like free (or quasi-free) markets are. Researchers are aware, that economics is a study of human behavior, but lack of a proper formal tool has shifted research in economics into the language of money, production, consumption, etc. From an economic point of view, when analyzing free (quasi-free) markets, more important is group behavior than individual behavior because they result in changes of market indexes. Group behavior leads in specific cases to the emergence of "group intelligence" with the most famous case named "A. Smith invisible hand of market". A computational model of Collective Intelligence allows for the formal extraction of the "system of inference processes" which run in an unconscious way in socio-economic structures. The construction of a proper formal and simulation model of such Collective Intelligence inferences allows us to take an attempt to predict outcomes in terms of economical results. The paper will present a formal basis, methodology of constructing Collective Intelligence systems for given socio-economic structures. (original abstract)
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Bibliografia
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  1. Berry, G., Boudol, G. (1992), The chemical abstract machine, Theoretical Computer Science.
  2. Fontana, W., Buss, L. W. (1994), The arrival of the fittest, Bulletin of Mathematical Biology 56(1), 1-64.
  3. Giarratano, J., Riley, G. (1998), Expert systems, PWS Pub. III ed.
  4. Prokhorov, A. B. (2001), Nonlinear Dynamics and Chaos Theory in Economics: a Historical Perspective, https://www.msu.edu/~prohorov/paper.pdf.
  5. Szuba, T. (1998), A Molecular Quasi-random Model of Computations Applied to Evaluate Collective Intelligence, Future Generation Computing Journal 14(5-6), 321-339.
  6. Szuba, T. (2001a), A formal definition of the phenomenon of collective intelligence and its IQ measure, Future Generation Computing Journal 17(4), 489-500, Elsevier.
  7. Szuba, T. (2001b), Computational Collective Intelligence, Wiley Series on Parallel and Distributed Computing. Wiley & Sons, February, 2001.
  8. Skrzyński, P. (2011), Collective Intelligence theory applied to describe phenomena of A. Smith invisible hand of market. Ph. D. dissertation. AGH Univ., January, 2011.
Cytowane przez
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ISSN
2300-7087
Język
eng
URI / DOI
http://dx.doi.org/10.7494/dmms.2012.6.1.41
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