Individual Q-Learning in Normal Form Games
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[1] S. Hart,et al. A Reinforcement Procedure Leading to Correlated Equilibrium , 2001 .
[2] S. Hart,et al. A simple adaptive procedure leading to correlated equilibrium , 2000 .
[3] R. Pemantle,et al. Nonconvergence to Unstable Points in Urn Models and Stochastic Approximations , 1990 .
[4] A. Roth,et al. Learning in Extensive-Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Term* , 1995 .
[5] N. Megiddo. On repeated games with incomplete information played by non-Bayesian players , 1980 .
[6] J. Harsanyi. Games with randomly disturbed payoffs: A new rationale for mixed-strategy equilibrium points , 1973 .
[7] Dimitri P. Bertsekas,et al. Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems , 1996, NIPS.
[8] Michael L. Littman,et al. Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach , 1993, NIPS.
[9] S. Vajda. Some topics in two-person games , 1971 .
[10] S. Hart,et al. Uncoupled Dynamics Cannot Lead to Nash Equilibrium ∗ , 2002 .
[11] James Hannan,et al. 4. APPROXIMATION TO RAYES RISK IN REPEATED PLAY , 1958 .
[12] A. Banos. On Pseudo-Games , 1968 .
[13] H. Chen,et al. STOCHASTIC APPROXIMATION PROCEDURES WITH RANDOMLY VARYING TRUNCATIONS , 1986 .
[14] S. Hart,et al. Uncoupled Dynamics Do Not Lead to Nash Equilibrium , 2003 .
[15] H. Peyton Young,et al. Learning, hypothesis testing, and Nash equilibrium , 2003, Games Econ. Behav..
[16] M. Hirsch,et al. Mixed Equilibria and Dynamical Systems Arising from Fictitious Play in Perturbed Games , 1999 .
[17] Ulrich Berger,et al. Fictitious play in 2×n games , 2005, J. Econ. Theory.
[18] Nicolò Cesa-Bianchi,et al. Gambling in a rigged casino: The adversarial multi-armed bandit problem , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.
[19] R. Aumann. Subjectivity and Correlation in Randomized Strategies , 1974 .
[20] Carlos S. Kubrusly,et al. Stochastic approximation algorithms and applications , 1973, CDC 1973.
[21] J. Nash. Equilibrium Points in N-Person Games. , 1950, Proceedings of the National Academy of Sciences of the United States of America.
[22] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[23] Daphne Koller,et al. Multi-Agent Influence Diagrams for Representing and Solving Games , 2001, IJCAI.
[24] Philip Wolfe,et al. Contributions to the theory of games , 1953 .
[25] Michael L. Littman,et al. An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games , 2001, NIPS.
[26] Josef Hofbauer,et al. Learning in perturbed asymmetric games , 2005, Games Econ. Behav..
[27] J M Smith,et al. Evolution and the theory of games , 1976 .
[28] Manuela M. Veloso,et al. Multiagent learning using a variable learning rate , 2002, Artif. Intell..
[29] Andrew G. Barto,et al. Elevator Group Control Using Multiple Reinforcement Learning Agents , 1998, Machine Learning.
[30] O. H. Brownlee,et al. ACTIVITY ANALYSIS OF PRODUCTION AND ALLOCATION , 1952 .
[31] M. Benaïm. Dynamics of stochastic approximation algorithms , 1999 .
[32] J. Jordan. Three Problems in Learning Mixed-Strategy Nash Equilibria , 1993 .
[33] Tilman Börgers,et al. Learning Through Reinforcement and Replicator Dynamics , 1997 .
[34] E. J. Collins,et al. Convergent multiple-timescales reinforcement learning algorithms in normal form games , 2003 .
[35] Arthur J. Robson,et al. A short proof of Harsanyi's purification theorem , 2003, Games Econ. Behav..
[36] D. Fudenberg,et al. The Theory of Learning in Games , 1998 .
[37] Paul Glimcher,et al. Physiological utility theory and the neuroeconomics of choice , 2005, Games Econ. Behav..
[38] Vivek S. Borkar,et al. Reinforcement Learning in Markovian Evolutionary Games , 2002, Adv. Complex Syst..