Hierarchical Policy Gradient Algorithms

Proceedings, Twentieth International Conference on Machine Learning

Volumn 1, Issue , 2003, Pages 226-233

  Ghavamzadeh, Mohammad ^a   Mahadevan, Sridhar ^a  

^a Biologically Inspired Neural and Dynamical Systems Laboratory   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; DECISION MAKING; HIERARCHICAL SYSTEMS; OPTIMAL SYSTEMS; PARAMETER ESTIMATION; PROBLEM SOLVING; STOCHASTIC CONTROL SYSTEMS;

HIERARCHICAL POLICY GRADIENT (HPG) ALGORITHMS; NON-PRIMITIVE SUBTASKS; POLICY GRADIENT REINFORCEMENT LEARNING; VALUE FUNCTION-BASED REINFORCEMENT LEARNING (VFRL);

LEARNING SYSTEMS;

EID: 1942452721     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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3. Ghavamzadeh, M., & Mahadevan, S. (2001). Continuous-time hierarchical reinforcement learning. Proceedings of the Eighteenth International Conference on Machine Learning (pp. 186-193).
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8. Parr, R. (1998). Hierarchical control and learning for Markov decision processes. Doctoral dissertation, University of California, Berkeley.
9. Sutton, R., Precup, D., & Singh, S. (1999). Between MDPs and Semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 112, 181-211.