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
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;
Conference_Titel :
Intelligent Agent (IA), 2011 IEEE Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-61284-059-8
DOI :
10.1109/IA.2011.5953618