• DocumentCode
    2292837
  • Title

    Expected payoff analysis of dynamic mixed strategies in an adversarial domain

  • Author

    Villacorta, Pablo J. ; Pelta, David A.

  • Author_Institution
    Dept. of Comput. Sci. & AI, Univ. of Granada, Granada, Spain
  • fYear
    2011
  • fDate
    11-15 April 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Adversarial decision making is aimed at determining optimal decision strategies to deal with an adversarial and adaptive opponent. One defense against this adversary is to make decisions that are intended to confuse him, although our rewards can be diminished. In this contribution, we describe ongoing research in the design of time varying decision strategies for a a simple adversarial model. The strategies obtained are compared against static strategies from a theoretical and empirical point of view. The results show encouraging improvements that open new venues for research.
  • Keywords
    decision making; inference mechanisms; adaptive opponent; adversarial decision making; adversarial domain; dynamic mixed strategy; optimal decision strategies; payoff analysis; static strategies; time varying decision strategies; Analytical models; Cognition; Computational modeling; Game theory; Games; Optimization; Adversarial reasoning; decision making; decision strategies;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Agent (IA), 2011 IEEE Symposium on
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-61284-059-8
  • Type

    conf

  • DOI
    10.1109/IA.2011.5953618
  • Filename
    5953618