On the conflict between inducing confusion and attaining payoff in adversarial decision making

Adversarial decision making is aimed at determining optimal strategies against an adversarial and adaptive opponent. One defense against this intrusion into our cognitive process is to make decisions that are intended to confuse the observer, although our rewards can be diminished. In this work, we propose a mathematical framework that allows studying the balance between inducing confusion and attaining payoff in adversarial decision making. Computational experiments are performed to evaluate how the payoff and the number of correct predictions are affected by the strategies selected for each participant and by the number of decisions available.