暂无分享,去创建一个
[1] O. H. Brownlee,et al. ACTIVITY ANALYSIS OF PRODUCTION AND ALLOCATION , 1952 .
[2] Anatol Rapoport,et al. The 2x2 Game , 1976 .
[3] Philip Heidelberger,et al. Quantile Estimation in Dependent Sequences , 1984, Oper. Res..
[4] David M. Kreps,et al. Learning Mixed Equilibria , 1993 .
[5] Michael L. Littman,et al. Markov Games as a Framework for Multi-Agent Reinforcement Learning , 1994, ICML.
[6] Ariel Rubinstein,et al. A Course in Game Theory , 1995 .
[7] L. Shapley,et al. Fictitious Play Property for Games with Identical Interests , 1996 .
[8] D. Monderer,et al. A 2£ 2 Game without the Fictitious Play Property ⁄ , 1996 .
[9] H. Kuk. On equilibrium points in bimatrix games , 1996 .
[10] Craig Boutilier,et al. The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems , 1998, AAAI/IAAI.
[11] Michael P. Wellman,et al. Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm , 1998, ICML.
[12] Yishay Mansour,et al. Nash Convergence of Gradient Dynamics in General-Sum Games , 2000, UAI.
[13] Manuela M. Veloso,et al. Rational and Convergent Learning in Stochastic Games , 2001, IJCAI.
[14] Michael L. Littman,et al. Friend-or-Foe Q-learning in General-Sum Games , 2001, ICML.
[15] Robert Axelrod,et al. The Evolution of Strategies in the Iterated Prisoner's Dilemma , 2001 .
[16] Manuela M. Veloso,et al. Multiagent learning using a variable learning rate , 2002, Artif. Intell..
[17] James C. Spall,et al. Introduction to stochastic search and optimization - estimation, simulation, and control , 2003, Wiley-Interscience series in discrete mathematics and optimization.
[18] Robert Wilson,et al. A global Newton method to compute Nash equilibria , 2003, J. Econ. Theory.
[19] Gerald Tesauro,et al. Extending Q-Learning to General Adaptive Multi-Agent Systems , 2003, NIPS.
[20] Keith B. Hall,et al. Correlated Q-Learning , 2003, ICML.
[21] Michael P. Wellman,et al. Nash Q-Learning for General-Sum Stochastic Games , 2003, J. Mach. Learn. Res..
[22] Martin Zinkevich,et al. Online Convex Programming and Generalized Infinitesimal Gradient Ascent , 2003, ICML.
[23] Tim Hesterberg,et al. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control , 2004, Technometrics.
[24] Yoav Shoham,et al. New Criteria and a New Algorithm for Learning in Multi-Agent Systems , 2004, NIPS.
[25] Bikramjit Banerjee,et al. Performance Bounded Reinforcement Learning in Strategic Interactions , 2004, AAAI.
[26] Michael H. Bowling,et al. Convergence and No-Regret in Multiagent Learning , 2004, NIPS.
[27] Yoav Shoham,et al. Run the GAMUT: a comprehensive approach to evaluating game-theoretic algorithms , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..
[28] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[29] Yoav Shoham,et al. Learning against multiple opponents , 2006, AAMAS '06.
[30] Vincent Conitzer,et al. AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents , 2003, Machine Learning.
[31] Bikramjit Banerjee,et al. RVσ(t): a unifying approach to performance and convergence in online multiagent learning , 2006, AAMAS '06.
[32] Andrew McLennan,et al. Gambit: Software Tools for Game Theory , 2006 .
[33] Yoav Shoham,et al. If multi-agent learning is the answer, what is the question? , 2007, Artif. Intell..
[34] James C. Spall,et al. Introduction to Stochastic Search and Optimization. Estimation, Simulation, and Control (Spall, J.C. , 2007 .
[35] Tuomas Sandholm,et al. Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm , 2022 .
[36] Sandip Sen,et al. Evolutionary Tournament-Based Comparison of Learning and Non-Learning Algorithms for Iterated Games , 2007, J. Artif. Soc. Soc. Simul..
[37] Yoav Shoham,et al. Multiagent Systems - Algorithmic, Game-Theoretic, and Logical Foundations , 2009 .
[38] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .