• DocumentCode
    2165583
  • Title

    Asymmetry in learning automata playing multi-level games

  • Author

    Billard, Edward A.

  • Author_Institution
    Dept. of Math. & Comput. Sci., California State Univ., Hayward, CA, USA
  • Volume
    3
  • fYear
    1998
  • fDate
    11-14 Oct 1998
  • Firstpage
    2202
  • Abstract
    To achieve synergy, it is important for agents to form cooperative groups such that shared resources, strategies and information can be fully utilized. A game-theoretic model is presented in which agents decide whether it is beneficial to form groups and what actions to take within the chosen context. Learning automata are used to model this multi-level decision-making process. The results show that asymmetries in initialization and equilibria do not effect this process. With delayed information, both symmetric and asymmetric penalties lead to chaos but with different Lyapunov exponents
  • Keywords
    cooperative systems; distributed decision making; game theory; learning automata; Lyapunov exponents; agents; asymmetric penalties; asymmetries; chaos; cooperative groups; delayed information; game theory; learning automata; multi-level decision making process; multi-level games; symmetric penalties; Area measurement; Chaos; Computer science; Context modeling; Decision making; Delay; Game theory; Learning automata; Mathematics; Probability distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4778-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1998.724982
  • Filename
    724982