Catcher-Evader Games

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. PDF

Cite

Text

Li et al. "Catcher-Evader Games." International Joint Conference on Artificial Intelligence, 2016.

Markdown

[Li et al. "Catcher-Evader Games." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/li2016ijcai-catcher/)

BibTeX

@inproceedings{li2016ijcai-catcher,
  title     = {{Catcher-Evader Games}},
  author    = {Li, Yuqian and Conitzer, Vincent and Korzhyk, Dmytro},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {329-337},
  url       = {https://mlanthology.org/ijcai/2016/li2016ijcai-catcher/}
}