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Stochastic Model of Evolutionary and Immunological Multi-Agent Systems: Parallel Execution of Local Actions

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EN
Abstrakty
EN
The refined model for the biologically inspired agent-based computation systems EMAS and iEMAS conforming to the BDI standard is presented. Moreover, their evolution is expressed in the form of the stationary Markov chains. This paper generalizes the results obtained by Byrski and Schaefer [7] to a strongly desired case in which some agents’ actions can be executed in parallel. In order to find the Markov transition rule, the precise synchronization scheme was introduced, which allows to establish the stepwise stochastic evolution of the system. The crucial feature which allows to compute the probability transition function in case of parallel execution of local actions is the commutativity of their transition operators. Some abstract conditions expressing such a commutativity which allow to classify the agents’ actions as local or global are formulated and verified in a very simple way. The above-mentioned Markov model constitutes the basis of the asymptotic analysis of EMAS and iEMAS necessary to evaluate their search possibilities and efficiency.
Wydawca
Rocznik
Strony
325--348
Opis fizyczny
Bibliogr. 13 poz.
Twórcy
autor
autor
autor
  • Department of Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krak´ow, Poland, schaefer@agh.edu.pl
Bibliografia
  • [1] Back, T., Hammel, U., Schwefel, H.-P.: Evolutionary computation: Comments on the history and current state, IEEE Trans. on Evolutionary Computation, 1(1), 1997.
  • [2] Byrski, A., Kisiel-Dorohinicki, M.: Immunological selection mechanism in agent-based evolutionary computation, Intelligent Information Processing and Web Mining : proceedings of the international IIS: IIPWM '05 conference : Gdansk, Poland (M. A. Klopotek, S. T.Wierzchon, K. Trojanowski, Eds.), Advances in Soft Computing, Springer Verlag, 2005.
  • [3] Byrski, A., Kisiel-Dorohinicki,M.: Agent-Based Evolutionary and Immunological Optimization, Computational Science - ICCS 2007, 7th International Conference, Beijing, China, May 27 - 30, 2007, Proceedings, Springer, 2007.
  • [4] Byrski, A., Kisiel-Dorohinicki,M., Nawarecki, E.: Agent-Based Evolution of Neural Network Architecture, Proc. of the IASTED Int. Symp.: Applied Informatics (M. Hamza, Ed.), IASTED/ACTA Press, 2002.
  • [5] Byrski, A., Schaefer, R.: Immunological mechanism for asynchronous evolutionary computation boosting, ICMAM 2008 : European workshop on Intelligent Computational Methods and Applied Mathematics : an international forum for researches, teachers and students : Cracow, Poland, 2008.
  • [6] Byrski, A., Schaefer, R.: Formal Model for Agent-Based Asynchronous Evolutionary Computation, Proceedings of IEEE Congress on Evolutionary Computation 2009 (IEEE CEC 2009), IEEE Computational Intelligence Society, IEEE Press, Trondheim, Norway, 18-21 May 2009.
  • [7] Byrski, A., Schaefer, R.: Stochastic Model of Evolutionary and Immunological Multi-Agent Systems: Mutually Exclusive Actions, Fundamenta Informaticae, 94, 2009.
  • [8] Cantú-Paz, E.: A summary of research on parallel genetic algorithms, IlliGAL Report No. 95007. University of Illinois, 1995.
  • [9] Cetnarowicz, K., Kisiel-Dorohinicki,M., Nawarecki, E.: The application of evolution process in multi-agent world (MAW) to the prediction system, Proc. of the 2nd Int. Conf. on Multi-Agent Systems (ICMAS'96) (M. Tokoro, Ed.), AAAI Press, 1996.
  • [10] Jennings, N. R., Sycara, K., Wooldridge, M.: A Roadmap of Agent Research and Development, Journal of Autonomous Agents and Multi-Agent Systems, 1(1), 1998, 7-38.
  • [11] Jennings, N. R., Wooldridge,M. J.: Software Agents, IEE Review, 1996, 17-20.
  • [12] Kisiel-Dorohinicki, M.: Agent-Oriented Model of Simulated Evolution, SofSem 2002: Theory and Practice of Informatics (W. I. Grosky, F. Plasil, Eds.), 2540, Springer-Verlag, 2002.
  • [13] Michalewicz, Z.: Genetic Algorithms Plus Data Structures Equals Evolution Programs, Springer-Verlag New York, Inc., Secaucus, NJ, USA, 1994, ISBN 0387580905.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0005-0083
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