%0 Conference Paper %B International Conference on Autonomous Agents and Multiagent Systems (AAMAS) [SHORT PAPER] %D 2013 %T Modeling Human Adversary Decision Making in Security Games: An Initial Report (Extended Abstract) %A Thanh H. Nguyen %A Azaria, Amos %A Pita, James %A Maheswaran, Rajiv %A Kraus, Sarit %A Tambe, Milind %X 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. %B International Conference on Autonomous Agents and Multiagent Systems (AAMAS) [SHORT PAPER] %G eng