@conference {1506247,
	title = {Addressing Execution and Observation Error in Security Games },
	booktitle = {AAAI{\textquoteright}11 Workshop on Applied Adversarial Reasoning and Risk Modeling (AARM)},
	year = {2011},
	abstract = {Attacker-defender Stackelberg games have become a popular
game-theoretic approach for security with deployments for
LAX Police, the FAMS and the TSA. Unfortunately, most of
the existing solution approaches do not model two key uncertainties of the real-world: there may be noise in the defender{\textquoteright}s
execution of the suggested mixed strategy and/or the observations made by an attacker can be noisy. In this paper, we analyze a framework to model these uncertainties, and demonstrate that previous strategies perform poorly in such uncertain settings. We also analyze RECON, a novel algorithm that
computes strategies for the defender that are robust to such
uncertainties, and explore heuristics that further improve RECON{\textquoteright}s efficiency.},
	author = {Jain, Manish and Yin, Zhengyu and Tambe, Milind and Ordonez, Fernando}
}
