Run the GAMUT: A Comprehensive Approach to Evaluating Game-Theoretic Algorithms
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
The complexity of computing a Nash equilibrium
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
The effect of collusion in congestion games
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Strong equilibrium in cost sharing connection games
Proceedings of the 8th ACM conference on Electronic commerce
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Approximability and Parameterized Complexity of Minmax Values
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Settling the complexity of computing two-player Nash equilibria
Journal of the ACM (JACM)
Mixed-integer programming methods for finding Nash equilibria
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
On Strong Equilibria in the Max Cut Game
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Approximate strong equilibrium in job scheduling games
Journal of Artificial Intelligence Research
Local search techniques for computing equilibria in two-player general-sum strategic-form games
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Strong and correlated strong equilibria in monotone congestion games
WINE'06 Proceedings of the Second international conference on Internet and Network Economics
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Computing equilibria of games is a central task in computer science. A large number of results are known for Nash equilibrium (NE). However, these can be adopted only when coalitions are not an issue. When instead agents can form coalitions, NE is inadequate and an appropriate solution concept is strong Nash equilibrium (SNE). Few computational results are known about SNE. In this paper, we first study the problem of verifying whether a strategy profile is an SNE, showing that the problem is in P. We then design a spatial branch--and--bound algorithm to find an SNE, and we experimentally evaluate the algorithm.