Integer programming vs. expert systems: an experimental comparison
Communications of the ACM
Achieving network optima using Stackelberg routing strategies
IEEE/ACM Transactions on Networking (TON)
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Sharing the cost of multicast transmissions
Journal of Computer and System Sciences - Special issue on Internet algorithms
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Multi-agent algorithms for solving graphical games
Eighteenth national conference on Artificial intelligence
Pure Nash equilibria: hard and easy games
Proceedings of the 9th conference on Theoretical aspects of rationality and knowledge
Reducibility among equilibrium problems
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Computing pure nash equilibria in graphical games via markov random fields
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Nash equilibria in graphical games on trees revisited
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
On the severity of Braess's paradox: designing networks for selfish users is hard
Journal of Computer and System Sciences - Special issue on FOCS 2001
Simple search methods for finding a Nash equilibrium
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A continuation method for Nash equilibria in structured games
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Graphical models for game theory
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
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Considerable progress has been made in recent years in complexity analysis of Nash equilibrium, so we restrict our attention to seek it from the empirical perspective in this paper. Based on a new description format of game - stimulate - response pair proposed in the paper, we put forward a constraints satisfaction-based algorithm on this data structure to compute pure Nash equilibrium of graphical game. And then, we discuss how to employ search strategies when finding the equilibrium in different types. To evaluate our algorithm, we use a comprehensive game generator - GAMUT, to produce a mass of data and take a famous tool - gambit as competitor. At last the experimental result is presented.