Online Skill Discovery using Graph-based Clustering
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[1] Shie Mannor,et al. Dynamic abstraction in reinforcement learning via clustering , 2004, ICML.
[2] Shie Mannor,et al. Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning , 2002, ECML.
[3] Pattie Maes,et al. Emergent Hierarchical Control Structures: Learning Reactive/Hierarchical Relationships in Reinforcement Environments , 1996 .
[4] Sridhar Mahadevan,et al. Recent Advances in Hierarchical Reinforcement Learning , 2003, Discret. Event Dyn. Syst..
[5] Andrew G. Barto,et al. Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining , 2009, NIPS.
[6] Doina Precup,et al. Temporal abstraction in reinforcement learning , 2000, ICML 2000.
[7] William W. Cohen,et al. Proceedings of the 23rd international conference on Machine learning , 2006, ICML 2008.
[8] Andrew G. Barto,et al. Using relative novelty to identify useful temporal abstractions in reinforcement learning , 2004, ICML.
[9] Alicia P. Wolfe,et al. Identifying useful subgoals in reinforcement learning by local graph partitioning , 2005, ICML.
[10] Andrew G. Barto,et al. Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density , 2001, ICML.
[11] Peter Stone,et al. The utility of temporal abstraction in reinforcement learning , 2008, AAMAS.
[12] Andrew G. Barto,et al. Skill Characterization Based on Betweenness , 2008, NIPS.
[13] Jean-Arcady Meyer,et al. Learning Hierarchical Control Structures for Multiple Tasks and Changing Environments , 1998 .
[14] Doina Precup,et al. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning , 1999, Artif. Intell..
[15] MahadevanSridhar,et al. Recent Advances in Hierarchical Reinforcement Learning , 2003 .