Using temporal neighborhoods to adapt function approximators in reinforcement learning

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

Volumn 1606, Issue , 1999, Pages 488-496

  Matthew Kretchmar, R ^a   Anderson, Charles W ^a  

^a Colorado State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUNCTIONS;

BASIS FUNCTIONS; COMPUTATIONAL RESOURCES; CURSE OF DIMENSIONALITY; FUNCTION APPROXIMATORS; INTRA-GROUP; LEARNING PROCESS; ON-LINE SAMPLING; VALUE FUNCTIONS;

REINFORCEMENT LEARNING;

EID: 84957661928     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/BFb0098206     Document Type: Conference Paper

References (10)

1. Charles W. Anderson. Q-Learning with Hidden-Unit Restarting. Advances in Neural Information Processing Systems, volume 5, S. J. Hanson, J. D. Cowan, and C. L. Giles, eds., Morgan Kaufinann Publishers, San Mateo, CA, pp. 81-88
2. Andrew G. Barto, and Richard S. Sutton. Reinforcement Learning: An Introduction. MIT Press, Cambridge, MA. 1988
3. Leslie Pack Kaclbling, Michael L. Littman, and Andrew W. Moore. Reinforcement Learning: A Survey. Journal of Artificial Intelligence Research: 4, May 1996
4. R. Matthew Kretchmar and Charles W. Anderson. Comparison of CMACs and Radial Basis Functions for Local Function Approximators in Reinforcement Learning. Proceedings of the International Conference on Neural Networks. 1997
5. R. Andrew McCallum. Using Transitional Proximity for Faster Reinforcement Learning. International Conference on Machine Learning, 1992
6. Andrew W. Moore. The Patti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces. Machine Learning: 21, 1995
7. Satindcr P. Singh, Tommi Jaakkola, and Michael I. Jordan. Reinforcement Learning with Soft State Aggregation. NIPS94, 1994
8. Richard S. Sutton. Learning to Predict by the Methods of Temporal Differences. Machine Learning:3, 1988
9. John N. Tsitsiklis, and Benjamin Van Roy. An Analysis of Temporal-Difference Learning with Function Approximation. IEEE Transactions on Automatic Control, Vol. 42, No. 5, May 1997
10. Bruce A. Whitehead, and Timothy D. Choate. Cooperative-Competitive Genetic Evohttion of Radial Basis bSmction Ccntcrs and Widths for Time Series Prediction. EEE Transactions on Neural Networks, Vol 7, No 4. July 1996.