Proceedings

Catcher-Evader Games

Yuqian Li, Vincent Conitzer, Dmytro Korzhyk

Download BibTeX Cite

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 329-336.

Abstract

Algorithms for computing game-theoretic solutions have recently been applied to a number of security domains. However, many of the techniques developed for compact representations of security games do not extend to Bayesian security games, which allow us to model uncertainty about the attacker's type. In this paper, we introduce a general framework of catcher-evader games that can capture Bayesian security games as well as other game families of interest. We show that computing Stackelberg strategies is NP-hard, but give an algorithm for computing a Nash equilibrium that performs well in experiments. We also prove that the Nash equilibria of these games satisfy the interchangeability property, so that equilibrium selection is not an issue.

Yuqian Li, Vincent Conitzer, and Dmytro Korzhyk. 2016. Catcher-Evader Games. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16. IJCAI, 329–336. https://ijcai.org/proceedings/2016/54
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards