@conference {1500406,
	title = {Equilibrium Refinement in Security Games with Arbitrary Scheduling Constraints },
	booktitle = {International Conference on Autonomous Agents and Multiagent Systems (AAMAS-18)},
	year = {2018},
	abstract = {Significant research effort in security games has focused in devising
strategies that perform well even when the attacker deviates from
optimal (rational) behavior. In most of these frameworks, a price
needs to be paid to ensure robustness against this unpredictability. However, equilibrium refinement is an attractive alternative to
boost solution robustness at no cost even though it has not received
as much attention in security game literature. In this framework,
resources are strategically allocated to secure an optimal outcome
against a rational adversary while simultaneously protecting other
targets to ensure good outcomes against boundedly rational or
constrained attackers. Unfortunately, existing approaches for equilibrium refinement in security games cannot effectively address
scheduling constraints that arise frequently in real-world applications. In this paper, we aim to fill this gap and make several key
contributions. First, we show that existing approaches for equilibrium refinement can fail in the presence of scheduling constraints.
Second, we investigate the properties of the best response of the attacker. Third, we leverage these properties to devise novel iterative
algorithms to compute the optimally refined equilibrium, with polynomially many calls to an LP oracle for zero-sum games. Finally, we
conduct extensive experimental evaluations that showcase i) the
superior performance of our approach in the face of a boundedly
rational attacker and ii) the attractive scalability properties of our
algorithm that can solve realistic-sized instances.},
	author = {Kai Wang and Qingyu Guo and Vayanos, Phebe and Tambe, Milind and An, Bo}
}
