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Matematicheskoe modelirovanie, 2008, Volume 20, Number 2, Pages 21–31 (Mi mm2146)  
This article is cited in 1 scientific paper (total in 1 paper)

Simulation of evolution of autonomous adaptive agents

O. P. Mosalova, V. G. Red'kob, D. V. Prokhorovc

a Moscow Institute of Physics and Technology
b Institute of Optical Neural Technologies, Russian Academy of Science
c Toyota Technical Center
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Abstract: A model of evolving populations of self-learning agents is studied and the interaction between learning and evolution is analyzed. Each agent is equipped with a neural network adaptive critic design for behavioral adaptation. The model is investigated for the case of a simple agent-broker that predicts stock price changes and uses its predictions for selecting actions. Three cases are analyzed in which either evolution or learning, or both, are active in this model. It is shown that the Baldwin effect can be observed in this model, viz., originally acquired adaptive policy of agents becomes inherited over the course of the evolution. Also the behavioral tactics of our agents is compared to the searching behavior of simple animals.
Received: 09.09.2006
English version:
Mathematical Models and Computer Simulations, 2009, Volume 1, Issue 1, Pages 156–164
DOI: https://doi.org/10.1134/S2070048209010177
Bibliographic databases:
Language: Russian
Citation: O. P. Mosalov, V. G. Red'ko, D. V. Prokhorov, “Simulation of evolution of autonomous adaptive agents”, Mat. Model., 20:2 (2008), 21–31; Math. Models Comput. Simul., 1:1 (2009), 156–164
Citation in format AMSBIB
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\by O.~P.~Mosalov, V.~G.~Red'ko, D.~V.~Prokhorov
\paper Simulation of evolution of autonomous adaptive agents
\jour Mat. Model.
\yr 2008
\vol 20
\issue 2
\pages 21--31
\mathnet{http://mi.mathnet.ru/mm2146}
\zmath{https://zbmath.org/?q=an:1150.68418}
\transl
\jour Math. Models Comput. Simul.
\yr 2009
\vol 1
\issue 1
\pages 156--164
\crossref{https://doi.org/10.1134/S2070048209010177}
\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-84929093174}
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  • https://www.mathnet.ru/eng/mm2146
  • https://www.mathnet.ru/eng/mm/v20/i2/p21
    • This publication is cited in the following 1 articles:
    1. Ekaterina A. Blagoveshchenskaya, Aleksandra I. Dashkina, Tatiana V. Lazovskaya, Viktoria V. Ryabukhina, Dmitriy A. Tarkhov, Lecture Notes in Computer Science, 9719, Advances in Neural Networks – ISNN 2016, 2016, 513  crossref
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Математическое моделирование
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    Abstract page:500
    Full-text PDF :142
    References:68
    First page:9
     
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