Existence of correlated equilibria
Mathematics of Operations Research
Time-dependent utility and action under uncertainty
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
On the complexity of the parity argument and other inefficient proofs of existence
Journal of Computer and System Sciences - Special issue: 31st IEEE conference on foundations of computer science, Oct. 22–24, 1990
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
On complexity as bounded rationality (extended abstract)
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Optimality and domination in repeated games with bounded players
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Finitely Repeated Games with Finite Automata
Mathematics of Operations Research
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Bargaining with limited computation: deliberation equilibrium
Artificial Intelligence
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
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The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Selection with monotone comparison costs
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Faster approximation algorithms for the minimum latency problem
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Dynamic Models of Deliberation and the Theory of Games
Proceedings of the 3rd Conference on Theoretical Aspects of Reasoning about Knowledge
Query strategies for priced information
Journal of Computer and System Sciences - Special issue on STOC 2000
Playing large games using simple strategies
Proceedings of the 4th ACM conference on Electronic commerce
Efficient algorithms for learning to play repeated games against computationally bounded adversaries
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Sorting and Selection with Structured Costs
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Strategic deliberation and truthful revelation: an impossibility result
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
The complexity of pure Nash equilibria
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Approximate Solutions for Partially Observable Stochastic Games with Common Payoffs
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Costly valuation computation in auctions
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
Mechanism design for computationally limited agents
Mechanism design for computationally limited agents
Computing correlated equilibria in multi-player games
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Computing equilibria in multi-player games
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Auction design with costly preference elicitation
Annals of Mathematics and Artificial Intelligence
Dynamic programming for partially observable stochastic games
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Complexity results about Nash equilibria
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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In traditional game theory, players are typically endowed with exogenously given knowledge of the structure of the game--either full omniscient knowledge or partial but fixed information. In real life, however, people are often unaware of the utility of taking a particular action until they perform research into its consequences. In this paper, we model this phenomenon. We imagine a player engaged in a question and- answer session, asking questions both about his or her own preferences and about the state of reality; thus we call this setting "Socratic" game theory. In a Socratic game, players begin with an a priori probability distribution over many possible worlds, with a different utility function for each world. Players can make queries, at some cost, to learn partial information about which of the possible worlds is the actual world, before choosing an action. We consider two query models: (1) an unobservable-query model, in which players learn only the response to their own queries, and (2) an observable-query model, in which players also learn which queries their opponents made.The results in this paper consider cases in which the underlying worlds of a two-player Socratic game are either constant-sum games or strategically zero-sum games, a class that generalizes constant-sum games to include all games in which the sum of payoffs depends linearly on the interaction between the players. When the underlying worlds are constant sum, we give polynomial-time algorithms to find Nash equilibria in both the observable- and unobservable-query models. When the worlds are strategically zero sum, we give efficient algorithms to find Nash equilibria in unobservablequery Socratic games and correlated equilibria in observablequery Socratic games.