@conference {1503286,
	title = {Modeling Human Adversary Decision Making in Security Games: An Initial Report (Extended Abstract) },
	booktitle = {International Conference on Autonomous Agents and Multiagent Systems (AAMAS) [SHORT PAPER]},
	year = {2013},
	abstract = {Motivated by recent deployments of Stackelberg security games
(SSGs), two competing approaches have emerged which either integrate models of human decision making into game-theoretic algorithms or apply robust optimization techniques that avoid adversary
modeling. Recently, a robust technique (MATCH) has been shown
to significantly outperform the leading modeling-based algorithms
(e.g., Quantal Response (QR)) even in the presence of significant
amounts of subject data. As a result, the effectiveness of using human behaviors in solving SSGs remains in question. We study this
question in this paper.},
	author = {Thanh H. Nguyen and Azaria, Amos and Pita, James and Maheswaran, Rajiv and Kraus, Sarit and Tambe, Milind}
}
