Capturing augmented sensing capabilities and intrusion delay in patrolling-intrusion games

Patrolling-intrusion games are recently receiving more and more attention in the literature. They are twoplayer non zero-sum games where an intruder tries to attack one place of interest and one patroller (or more) tries to capture the intruder. The patroller cannot completely cover the environment following a cycle, otherwise the intruder will successfully strike at least a target. Thus, the patroller employs a randomized strategy. These games are usually studied as leader-follower games, where the patroller is the leader and the intruder is the follower. The models proposed in the state of the art so far present several limitations that prevent their employment in realistic settings. In this paper, we refine the models from the state-of-the-art capturing patroller´s augmented sensing capabilities and a possible delay in the intrusion, we propose algorithms to solve efficiently our extensions, and we experimentally evaluate the computational time in some case studies.