Unleashing Dec-MDPs in Security Games: Enabling Effective Defender Teamwork

• Main Authors: Shieh, Eric, Jiang, Albert, Yadav, Amulya, VARAKANTHAM, Pradeep Reddy, Tambe, Milind
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Artificial Intelligence and Robotics; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/2641; https://ink.library.smu.edu.sg/context/sis_research/article/3641/viewcontent/ecai_main_decmdp_security_final.pdf
• Institution: Singapore Management University

Multiagent teamwork and defender-attacker security games are two areas that are currently receiving significant attention within multiagent systems research. Unfortunately, despite the need for effective teamwork among multiple defenders, little has been done to harness the teamwork research in security games. This paper is the first to remedy this situation by integrating the powerful teamwork mechanisms offered by Dec-MDPs into security games. We offer the following novel contributions in this paper: (i) New models of security games where a defender team’s pure strategy is defined as a DecMDP policy for addressing coordination under uncertainty; (ii) New algorithms based on column generation that enable efficient generation of mixed strategies given this new model; (iii) Handling global events during defender execution for effective teamwork; (iv) Exploration of the robustness of randomized pure strategies. The paper opens the door to a potentially new area combining computational game theory and multiagent teamwork.