Graphical Models for Game Theory
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Multi-agent algorithms for solving graphical games
Eighteenth national conference on Artificial intelligence
Playing large games using simple strategies
Proceedings of the 4th ACM conference on Electronic commerce
How much can taxes help selfish routing?
Proceedings of the 4th ACM conference on Electronic commerce
Pure Nash equilibria: hard and easy games
Proceedings of the 9th conference on Theoretical aspects of rationality and knowledge
Computing Nash equilibria of action-graph games
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Convergence time to Nash equilibrium in load balancing
ACM Transactions on Algorithms (TALG)
Convergence to approximate Nash equilibria in congestion games
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
On the complexity of constrained Nash equilibria in graphical games
Theoretical Computer Science
Agent influence as a predictor of difficulty for decentralized problem-solving
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Pure Nash equilibria: hard and easy games
Journal of Artificial Intelligence Research
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Convergence time to Nash equilibria
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
On honesty in sovereign information sharing
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
The complexity of approximate nash equilibrium in congestion games with negative delays
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
Scaling simulation-based game analysis through deviation-preserving reduction
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Pricing of parking for congestion reduction
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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We introduce a general representation of large-population games in which each player's influence on the others is centralized and limited, but may otherwise be arbitrary. This representation significantly generalizes the class known as congestion games in a natural way. Our main results are provably correct and efficient algorithms for computing and learning approximate Nash equilibria in this general framework.