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Evolutionary Method of Constructing Artificial Intelligence Systems

  • A. V. AnisimovEmail author
  • O. O. Marchenko
  • V. R. Zemlianskyi
CYBERNETICS
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Abstract

An evolutionary model of constructing artificial intelligence is presented, which is destined for designing and developing intelligent systems. The model allows describing a variety of subject areas with constructing knowledge bases. It has universal means to formally describe tasks and environments for implementing computational processes to solve them. The key basic element of the proposed model is the so-called ALF, i.e., an intelligent agent with the abilities to self-learning, communication, self-organization, and joint actions with similar agents. The development of ALF agents is based on evolutionary principles implemented using genetic algorithms. The proposed approach is implemented in the form of a game model. The developed structure and functionality of ALF agents stipulate the flexibility and efficiency of the model, which is confirmed by experiments.

Keywords

artificial intelligence multiagent system evolutionary programming 

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References

  1. 1.
    S. Nirenburg and V. Raskin, Ontological Semantics, MIT Press, Cambridge, MA (2004).Google Scholar
  2. 2.
    I. Bratko, Prolog Programming for Artificial Intelligence, Harlow, England; Addison Wesley, New York (2001).Google Scholar
  3. 3.
    M. Gardner, “Mathematical games — The fantastic combinations of John Conway’s new solitaire game ‘life’,” Scientific American, Vol. 223, 120–123 (1970).CrossRefGoogle Scholar
  4. 4.
    G. F. Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving [Russian translation], 4th Edition, Williams Publishing House, Moscow (2003).Google Scholar
  5. 5.
    S. J. Gould, Full House: The Spread of Excellence from Plato to Darwin, Harmony Books, New York (1996).CrossRefGoogle Scholar
  6. 6.
    J. Von Neumann and A. W. Burks, Theory of Self-Reproducing Automata, University of Illinois Press, Urbana (1966).Google Scholar
  7. 7.
    E. F. Codd, Cellular Automata, Academic Press, Orlando (1968).zbMATHGoogle Scholar
  8. 8.
    C. G. Langton, “Studying artificial life with cellular automata,” Physica D: Nonlinear Phenomena, Vol. 22, Issues 1–3, 120–149 (1986).MathSciNetCrossRefGoogle Scholar
  9. 9.
    R. Hightower, The Devore Universal Computer Constructor, Presentation at the Third Workshop of Artificial Life, Santa Fe, NM (1992).Google Scholar
  10. 10.
    R. A. Brooks, “Intelligence without reason,” in: Proc. 12th International Joint Conference on Artificial Intelligence (IJCAI-91), Sydney, Australia (1991), pp. 569–595.Google Scholar
  11. 11.
    N. J. Nilsson, “Teleo-reactive programs for agent control,” Journal of Artificial Intelligence Research, Vol. 1, No. 1, 139–158 (1993).Google Scholar
  12. 12.
    J. P. Crutchfield and M. Mitchell, “The evolution of emergent computation,” in: Proc. National Academy of Sciences of the United States of America, Vol. 92 (23), 10742–10746 (1995). DOI:  https://doi.org/10.1073/pnas.92.23.10742.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • A. V. Anisimov
    • 1
    Email author
  • O. O. Marchenko
    • 1
  • V. R. Zemlianskyi
    • 1
  1. 1.Taras Shevchenko National University of KyivKyivUkraine

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