Deep Residual Reinforcement Learning (Extended Abstract)
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Shimon Whiteson | Shangtong Zhang | Wendelin Boehmer | Shangtong Zhang | Wendelin Boehmer | Shimon Whiteson
[1] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[2] Richard S. Sutton,et al. Learning to predict by the methods of temporal differences , 1988, Machine Learning.
[3] Peter A. Flach,et al. Proceedings of the 28th International Conference on Machine Learning , 2011 .
[4] P. Schrimpf,et al. Dynamic Programming , 2011 .
[5] Sergey Levine,et al. Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning , 2018, ArXiv.
[6] Shalabh Bhatnagar,et al. Fast gradient-descent methods for temporal-difference learning with linear function approximation , 2009, ICML '09.
[7] V. Kaul,et al. Planning , 2012 .
[8] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[9] Peter Dayan,et al. Q-learning , 1992, Machine Learning.
[10] Leemon C. Baird,et al. Residual Algorithms: Reinforcement Learning with Function Approximation , 1995, ICML.
[11] Honglak Lee,et al. Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion , 2018, NeurIPS.
[12] R. Lathe. Phd by thesis , 1988, Nature.
[13] Roland Siegwart,et al. Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems , 2020, Adaptive Agents and Multi-Agent Systems.
[14] Marc G. Bellemare,et al. The Arcade Learning Environment: An Evaluation Platform for General Agents , 2012, J. Artif. Intell. Res..
[15] Pieter Abbeel,et al. Model-Ensemble Trust-Region Policy Optimization , 2018, ICLR.
[16] John N. Tsitsiklis,et al. Analysis of temporal-difference learning with function approximation , 1996, NIPS 1996.
[17] Martin L. Puterman,et al. Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .
[18] Shimon Whiteson,et al. Breaking the Deadly Triad with a Target Network , 2021, ICML.
[19] Shalabh Bhatnagar,et al. Toward Off-Policy Learning Control with Function Approximation , 2010, ICML.
[20] Herke van Hoof,et al. Addressing Function Approximation Error in Actor-Critic Methods , 2018, ICML.
[21] Richard S. Sutton,et al. Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming , 1990, ML.
[22] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[23] Lihong Li,et al. A worst-case comparison between temporal difference and residual gradient with linear function approximation , 2008, ICML '08.
[24] Martha White,et al. An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning , 2015, J. Mach. Learn. Res..