Dynamic vs. static decision strategies in adversarial reasoning

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 di- minished. It is assumed that making decisions in an uncertain envi- ronment is a hard task. However, this situation is of upmost interest in the case of adversarial reasoning as what we want is to force the presence of uncertainty in order to confuse the adversary in situa- tions of repeated conflicting encounters. Using simulations, the use of dynamic vs. static decision strategies is analyzed. The main con- clusions are: a) the use of the proposed dynamic strategies has sense, b) the presence of an adversary may produce a decrease of, at least, 45% with respect to the theoretical best payoff and c) the relation between this reduction and the way the uncertainty is forced should be further investigated.