Autonomous subgoal discovery and hierarchical abstraction for reinforcement learning using monte carlo method

Proceedings of the National Conference on Artificial Intelligence

Volumn 4, Issue , 2005, Pages 1588-1589

  Asadi, Mehran ^a   Huber, Manfred ^a  

^a University of Texas at Arlington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 29344448283     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

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5. Givan, R.; Leach, S.; and Dean, T. 2000. Bounded-parameter markov decision processes. Artificial Intelligence 122(1-2):71-109.
6. Goel, S., and Huber, M. 2003. Subgoal discovery for hierarchical reinforcement learning using learned policies. In In Proceedings of the 16th International FLAIRS Conference, 346-350. AAAI.
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8. McGovern, A., and Barto, A. 2001. Automatic discovery of subgoals in reinforcement learning using diverse density. In Proceedings of the 18th International Conference on Machine Learning, 361-368.
9. Parr, R. 1998. Hierarchical Control and Learning for Markov Decision Processes. Ph.D. Dissertation, University of California, Berkeley, C A.
10. Sutton, R.; Precup, D.; and Singh, S. 1999. Between MDPs and Semi-MDPs: Learning, planning, and representing knowledge at multiple temporal scales. Artificial Intelligence 112:181-211.