Emergent Information Technologies and Enabling Policies for Counter-Terrorism (IEEE Press Series on Computational Intelligence)
Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind
Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind
Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
On the conflict between inducing confusion and attaining payoff in adversarial decision making
Information Sciences: an International Journal
A Game-Theoretic Approach to Determining Efficient Patrolling Strategies for Mobile Robots
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Editorial: Modelling uncertainty
Information Sciences: an International Journal
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
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Adversarial decision making is aimed at finding strategies for dealing with an adversary who observes our decisions and tries to learn our behavior pattern. Based on a simple mathematical model, the present contribution provides analytical expressions for the expected payoff when using simple strategies which try to balance confusion and payoff. Additional insights are provided regarding the structure of the payoff matrix. Computational experiments show the agreement between theoretical expressions and empirical simulations, thus paving the way to make the assessment of new strategies easier.