Catcher-Evader Games

TL;DR

This paper introduces catcher-evader games as a versatile framework for Bayesian security games, providing algorithms for Nash equilibria computation and analyzing their properties, with practical experimental results.

Contribution

It extends security game models to Bayesian settings and offers a new algorithm for Nash equilibrium computation, addressing computational hardness.

Findings

Computing Stackelberg strategies is NP-hard.

An effective algorithm for Nash equilibrium computation is proposed.

Nash equilibria satisfy the interchangeability property.

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 {\em Bayesian} security games, which allow us to model uncertainty about the attacker's type. In this paper, we introduce a general framework of {\em 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 {\em interchangeability} property, so that equilibrium selection is not an issue.