# Defender Strategies In Domains Involving Frequent Adversary Interaction (Extended Abstract)

### Citation:

Fei Fang, Peter Stone, and Milind Tambe. 2015. “Defender Strategies In Domains Involving Frequent Adversary Interaction (Extended Abstract) .” In International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015).

### Abstract:

Recently, there has been an increase in interest in applying game theoretic approaches to domains involving frequent adversary interactions, such as wildlife and fishery protection. In these domains, the law enforcement agency faces adversaries who repeatedly and frequently carry out illegal activities, and thus, do not have time for extensive surveillance before taking actions. This makes them significantly different from counter-terrorism domains where game-theoretic approaches have been widely deployed. This paper presents a game-theoretic approach to be used by the defender in these Frequent Adversary Interaction (FAI) domains. We provide (i) a novel game model for FAI domains, describing the interaction between the defender and the attackers in a repeated game and (ii) algorithms that plan for the defender strategies to achieve high average expected utility over all rounds.