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

  • Authors:
  • David Pelta;Ronald R. Yager

  • Affiliations:
  • Models of Decision and Optimization Research Group, Department of Computer Science and A.I., University of Granada, C/Periodista Daniel Saucedo s/n, 18071 Granada, Spain;Machine Intelligence Institute, Iona College, New Rochelle, NY 10801, USA

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2009

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Abstract

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.