Learning Optimal Commitment to Overcome Insecurity

Game-theoretic algorithms for physical security have made an impressive realworld impact. These algorithms compute an optimal strategy for the defender to commit to in a Stackelberg game, where the attacker observes the defender's strategy and best-responds. In order to build the game model, though, the payoffs of potential attackers for various outcomes must be estimated; inaccurate estimates can lead to significant inefficiencies.