Computers, Chess, and Cognition
Computers, Chess, and Cognition
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Computing correlated equilibria in multi-player games
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Complexity of (iterated) dominance
Proceedings of the 6th ACM conference on Electronic commerce
On the Complexity of Two-PlayerWin-Lose Games
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
The complexity of computing a Nash equilibrium
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
The computational complexity of nash equilibria in concisely represented games
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
The influence of neighbourhood and choice on the complexity of finding pure Nash equilibria
Information Processing Letters
Pure Nash equilibria: hard and easy games
Journal of Artificial Intelligence Research
Spiteful bidding in sealed-bid auctions
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Current challenges in multi-player game search
CG'04 Proceedings of the 4th international conference on Computers and Games
Incentive compatible ranking systems
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Strategyproof deterministic lotteries under broadcast communication
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Efficiently exploiting symmetries in real time dynamic programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Rationality in the full-information model
TCC'10 Proceedings of the 7th international conference on Theory of Cryptography
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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We embark on an initial study of a new class of strategic (normal-form) games, so-called ranking games, in which the payoff to each agent solely depends on his position in a ranking of the agents induced by their actions. This definition is motivated by the observation that in many strategic situations such as parlor games, competitive economic scenarios, and some social choice settings, players are merely interested in performing optimal relative to their opponents rather than in absolute measures. A simple but important subclass of ranking games are single-winner games where in any outcome one agent wins and all others lose. We investigate the computational complexity of a variety of common game-theoretic solution concepts in ranking games and deliver hardness results for iterated weak dominance and mixed Nash equilibria when there are more than two players and pure Nash equilibria when the number of players is unbounded. This dashes hope that multi-player ranking games can be solved efficiently, despite the structural restrictions of these games.