Playing is believing: The role of beliefs in multi-agent learning
暂无分享,去创建一个
[1] Neri Merhav,et al. Universal prediction of individual sequences , 1992, IEEE Trans. Inf. Theory.
[2] Peter Stone,et al. Leading Best-Response Strategies in Repeated Games , 2001, International Joint Conference on Artificial Intelligence.
[3] John Nachbar,et al. Non-computable strategies and discounted repeated games , 1996 .
[4] Y. Freund,et al. Adaptive game playing using multiplicative weights , 1999 .
[5] Manuela M. Veloso,et al. Multiagent learning using a variable learning rate , 2002, Artif. Intell..
[6] Craig Boutilier,et al. The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems , 1998, AAAI/IAAI.
[7] Shin Ishii,et al. Multi-agent reinforcement learning: an approach based on the other agent's internal model , 2000, Proceedings Fourth International Conference on MultiAgent Systems.
[8] Neri Merhav,et al. Universal Prediction , 1998, IEEE Trans. Inf. Theory.
[9] Michael P. Wellman,et al. Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm , 1998, ICML.
[10] Michael L. Littman,et al. Friend-or-Foe Q-learning in General-Sum Games , 2001, ICML.
[11] D. Fudenberg,et al. Consistency and Cautious Fictitious Play , 1995 .
[12] Yishay Mansour,et al. Nash Convergence of Gradient Dynamics in General-Sum Games , 2000, UAI.
[13] Keith B. Hall,et al. Correlated Q-Learning , 2003, ICML.
[14] Michael L. Littman,et al. Markov Games as a Framework for Multi-Agent Reinforcement Learning , 1994, ICML.
[15] Y. Freund,et al. The non-stochastic multi-armed bandit problem , 2001 .