Computing the optimal strategy to commit to
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Leader-follower strategies for robotic patrolling in environments with arbitrary topologies
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Computing optimal randomized resource allocations for massive security games
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
GUARDS and PROTECT: next generation applications of security games
ACM SIGecom Exchanges
Computing time-dependent policies for patrolling games with mobile targets
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
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Defender-Attacker Stackelberg games are the foundations of tools deployed for computing optimal patrolling strategies in adversarial domains such as the United states Federal Air Marshals Service and the United States Coast Guard, among others. In Stackelberg game models of these systems the attacker knows only the probability that each target is covered by the defender, but is oblivious to the detailed timing of the coverage schedule. In many real-world situations, however, the attacker can observe the current location of the defender and can exploit this knowledge to reason about the defender's future moves. We study Stackelberg security games in which the defender sequentially moves between targets, with moves constrained by an exogenously specified graph, while the attacker can observe the defender's current location and his (stochastic) policy concerning future moves.