Hierarchical Reinforcement Learning in Partially Observable Markovian Environments
暂无分享,去创建一个
[1] Kenichi Abe,et al. Switching Q-learning in partially observable Markovian environments , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).
[2] Leslie Pack Kaelbling,et al. Learning Policies for Partially Observable Environments: Scaling Up , 1997, ICML.
[3] Michael L. Littman,et al. Memoryless policies: theoretical limitations and practical results , 1994 .
[4] Leslie Pack Kaelbling,et al. Acting Optimally in Partially Observable Stochastic Domains , 1994, AAAI.
[5] Tom M. Mitchell,et al. Reinforcement learning with hidden states , 1993 .
[6] Andrew McCallum,et al. Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State , 1995, ICML.
[7] Ron Sun,et al. Self-segmentation of sequences: automatic formation of hierarchies of sequential behaviors , 2000, IEEE Trans. Syst. Man Cybern. Part B.
[8] Lonnie Chrisman,et al. Reinforcement Learning with Perceptual Aliasing: The Perceptual Distinctions Approach , 1992, AAAI.
[9] Richard S. Sutton,et al. Reinforcement learning with replacing eligibility traces , 2004, Machine Learning.
[10] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..