Speeding-up reinforcement learning with multi-step actions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2415 LNCS, Issue , 2002, Pages 813-818

  Schoknecht, Ralf ^a   Riedmiller, Martin ^a  

^a UNIVERSITY OF KARLSRUHE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; MACHINE LEARNING; NEURAL NETWORKS; TIME MEASUREMENT;

BENCH-MARK PROBLEMS; DIFFERENT TIME SCALE; LEARNING SPEED; MULTI-STEP; SPECIAL STRUCTURE; SUBTASKS; TEMPORAL ABSTRACTION; TIME-SCALES; HEIDELBERG;

REINFORCEMENT LEARNING;

EID: 35248820427     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-46084-5_132     Document Type: Conference Paper

References (6)

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2. A. McGovern, R.S. Sutton, and A.H. Fagg. Roles of macro-actions in accelerating reinforcement learning. In Grace Hopper Celebration of Women in Computing, 1997.
3. S. Pareigis. Adaptive choice of grid and time in reinforcement learning. In Advances in Neural Information Processing Systems, volume 10. MIT Press, 1998.
4. R. E. Parr. Hierarchical Control and Learning for Markov Decision Processes. PhD thesis, University of California, Berkeley, CA, 1998.
5. T. J. Perkins and D. Precup. Using options for knowledge transfer in reinforcement learning. Technical report, University of Massachusetts, Amherst, 1999.
6. R. S. Sutton, D. Precup, and S. Singh. Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 112:181-211, 1999.