Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track
Computing optimal randomized resource allocations for massive security games
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Stackelberg vs. Nash in security games: interchangeability, equivalence, and uniqueness
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
GUARDS: game theoretic security allocation on a national scale
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
A double oracle algorithm for zero-sum security games on graphs
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Quality-bounded solutions for finite Bayesian Stackelberg games: scaling up
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned
Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned
Improving resource allocation strategy against human adversaries in security games
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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Security and sustainability are two critical global challenges that involve the interaction of many intelligent actors. Game theory provides a sound mathematical framework to model such interactions, and computational game theory in particular has a promising role to play in helping to address key aspects of these challenges. Indeed, in the domain of security, we have already taken some encouraging steps by successfully applying game-theoretic algorithms to real-world security problems: our algorithms are in use by agencies such as the US coast guard, the Federal Air Marshals Service, the LAX police and the Transportation Security Administration. While these applications of game-theoretic algorithms have advanced the state of the art, this paper lays out some key challenges as we continue to expand the use of these algorithms in real-world domains. One such challenge in particular is that classical game theory makes a set of assumptions of the players, which may not be consistent with real-world scenarios, especially when humans are involved. To actually model human behavior within game-theoretic framework, it is important to address the new challenges that arise due to the presence of human players: (i) human bounded rationality; (ii) limited observations and imperfect strategy execution; (iii) large action spaces. We present initial solutions to these challenges in context of security games. For sustainability, we lay out our initial efforts and plans, and key challenges related to human behavior in the loop.