Opponent Modeling in Deep Reinforcement Learning
暂无分享,去创建一个
[1] Geoffrey E. Hinton,et al. Adaptive Mixtures of Local Experts , 1991, Neural Computation.
[2] Michael L. Littman,et al. Markov Games as a Framework for Multi-Agent Reinforcement Learning , 1994, ICML.
[3] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[4] Jonathan Schaeffer,et al. Opponent Modeling in Poker , 1998, AAAI/IAAI.
[5] Richard S. Sutton,et al. Introduction to Reinforcement Learning , 1998 .
[6] William T. B. Uther,et al. Adversarial Reinforcement Learning , 2003 .
[7] Michael H. Bowling,et al. Bayes' Bluff: Opponent Modelling in Poker , 2005, UAI 2005.
[8] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[9] Pieter Spronck,et al. Opponent Modeling in Real-Time Strategy Games , 2007, GAMEON.
[10] Risto Miikkulainen,et al. Evolving explicit opponent models in game playing , 2007, GECCO '07.
[11] Mark Richards,et al. Opponent Modeling in Scrabble , 2007, IJCAI.
[12] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[13] Tuomas Sandholm,et al. Game theory-based opponent modeling in large imperfect-information games , 2011, AAMAS.
[14] Ian D. Watson,et al. On Combining Decisions from Multiple Expert Imitators for Performance , 2011, IJCAI.
[15] Jordan L. Boyd-Graber,et al. Besting the Quiz Master: Crowdsourcing Incremental Classification Games , 2012, EMNLP.
[16] Michael H. Bowling,et al. Online implicit agent modelling , 2013, AAMAS.
[17] Marc'Aurelio Ranzato,et al. Learning Factored Representations in a Deep Mixture of Experts , 2013, ICLR.
[18] Alex Graves,et al. Recurrent Models of Visual Attention , 2014, NIPS.
[19] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[20] Peter Stone,et al. Deep Recurrent Q-Learning for Partially Observable MDPs , 2015, AAAI Fall Symposia.
[21] Sergey Levine,et al. Learning deep neural network policies with continuous memory states , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[22] Shimon Whiteson,et al. Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks , 2016, ArXiv.
[23] Dorian Kodelja,et al. Multiagent cooperation and competition with deep reinforcement learning , 2015, PloS one.