%0 Conference Paper %B Conference on Artificial Intelligence (AAAI) Spotlight Track %D 2012 %T PROTECT: An Application of Computational Game Theory for the Security of the Ports of the United States %A Shieh, Eric %A An, Bo %A Yang, Rong %A Tambe, Milind %A Baldwin, Craig %A Joseph DiRenzo %A Maule, Ben %A Meyer, Garrett %X Building upon previous security applications of computational game theory, this paper presents PROTECT, a gametheoretic system deployed by the United States Coast Guard (USCG) in the port of Boston for scheduling their patrols. USCG has termed the deployment of PROTECT in Boston a success, and efforts are underway to test it in the port of New York, with the potential for nationwide deployment. PROTECT is premised on an attacker-defender Stackelberg game model and offers five key innovations. First, this system is a departure from the assumption of perfect adversary rationality noted in previous work, relying instead on a quantal response (QR) model of the adversary’s behavior — to the best of our knowledge, this is the first real-world deployment of the QR model. Second, to improve PROTECT’s efficiency, we generate a compact representation of the defender’s strategy space, exploiting equivalence and dominance. Third, we show how to practically model a real maritime patrolling problem as a Stackelberg game. Fourth, our experimental results illustrate that PROTECT’s QR model more robustly handles real-world uncertainties than a perfect rationality model. Finally, in evaluating PROTECT, this paper provides realworld data: (i) comparison of human-generated vs PROTECT security schedules, and (ii) results from an Adversarial Perspective Team’s (human mock attackers) analysis. %B Conference on Artificial Intelligence (AAAI) Spotlight Track %G eng