暂无分享,去创建一个
Rahul Savani | Gregory Palmer | Karl Tuyls | Daan Bloembergen | K. Tuyls | Rahul Savani | D. Bloembergen | Gregory Palmer
[1] Hado van Hasselt,et al. Double Q-learning , 2010, NIPS.
[2] Panagiotis Tzionas,et al. A robust approach for multi-agent natural resource allocation based on stochastic optimization algorithms , 2014, Appl. Soft Comput..
[3] Gerhard Weiss,et al. Multiagent Learning: Basics, Challenges, and Prospects , 2012, AI Mag..
[4] Jonathan P. How,et al. Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability , 2017, ICML.
[5] Moses Charikar,et al. Similarity estimation techniques from rounding algorithms , 2002, STOC '02.
[6] Tom Schaul,et al. Reinforcement Learning with Unsupervised Auxiliary Tasks , 2016, ICLR.
[7] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[8] Karl Tuyls,et al. Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective , 2008, J. Mach. Learn. Res..
[9] Rudolf Paul Wiegand,et al. An analysis of cooperative coevolutionary algorithms , 2004 .
[10] David Silver,et al. Deep Reinforcement Learning with Double Q-Learning , 2015, AAAI.
[11] Jonathan P. How,et al. Deep Decentralized Multi-task Multi-Agent RL under Partial Observability , 2017 .
[12] Sean Luke,et al. Lenient Learning in Independent-Learner Stochastic Cooperative Games , 2016, J. Mach. Learn. Res..
[13] Guy Lever,et al. Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward , 2018, AAMAS.
[14] Karl Tuyls,et al. Evolutionary Dynamics of Multi-Agent Learning: A Survey , 2015, J. Artif. Intell. Res..
[15] Long Ji Lin,et al. Self-improving reactive agents based on reinforcement learning, planning and teaching , 1992, Machine Learning.
[16] Bart De Schutter,et al. Multi-agent Reinforcement Learning: An Overview , 2010 .
[17] Sergey Levine,et al. Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[18] Filip De Turck,et al. #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning , 2016, NIPS.
[19] Tucker R. Balch,et al. Communication in reactive multiagent robotic systems , 1995, Auton. Robots.
[20] Tilman Börgers,et al. Learning Through Reinforcement and Replicator Dynamics , 1997 .
[21] Bart De Schutter,et al. A Comprehensive Survey of Multiagent Reinforcement Learning , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[22] Dorian Kodelja,et al. Multiagent cooperation and competition with deep reinforcement learning , 2015, PloS one.
[23] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[24] Shimon Whiteson,et al. Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning , 2017, ICML.
[25] Guillaume J. Laurent,et al. Hysteretic q-learning :an algorithm for decentralized reinforcement learning in cooperative multi-agent teams , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[26] Karl Tuyls,et al. The importance of experience replay database composition in deep reinforcement learning , 2015 .
[27] Ann Nowé,et al. Evolutionary game theory and multi-agent reinforcement learning , 2005, The Knowledge Engineering Review.
[28] Guillaume Lample,et al. Playing FPS Games with Deep Reinforcement Learning , 2016, AAAI.
[29] Richard S. Sutton,et al. Introduction to Reinforcement Learning , 1998 .
[30] Tom Schaul,et al. Prioritized Experience Replay , 2015, ICLR.
[31] Kenneth A. De Jong,et al. A Cooperative Coevolutionary Approach to Function Optimization , 1994, PPSN.
[32] Mykel J. Kochenderfer,et al. Cooperative Multi-agent Control Using Deep Reinforcement Learning , 2017, AAMAS Workshops.
[33] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[34] Pablo Hernandez-Leal,et al. A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity , 2017, ArXiv.
[35] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[36] Wei Zhang,et al. Multiagent-Based Reinforcement Learning for Optimal Reactive Power Dispatch , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[37] Guillaume J. Laurent,et al. Independent reinforcement learners in cooperative Markov games: a survey regarding coordination problems , 2012, The Knowledge Engineering Review.
[38] Sean Luke,et al. Lenient learners in cooperative multiagent systems , 2006, AAMAS '06.
[39] Peter Dayan,et al. Q-learning , 1992, Machine Learning.
[40] Karl Tuyls,et al. Empirical and theoretical support for lenient learning , 2011, AAMAS.