Adaptive Choice of Grid and Time in Reinforcement Learning (1997)

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by Stephan Pareigis
Venue:IN NIPS ’97: PROCEEDINGS OF THE 1997 CONFERENCE ON ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 10
Citations:16 - 1 self

Active Bibliography

Numerical Schemes for the Continuous Q-function of Reinforcement Learning – Stephan Pareigis
808 USER’S GUIDE TO VISCOSITY SOLUTIONS OF SECOND ORDER PARTIAL DIFFERENTIAL EQUATIONS – Michael G. Crandall, Hitoshi Ishii, Pierre-louis Lions - 1992
1405 Reinforcement learning: a survey – Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore - 1996
460 Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning – Richard Sutton, Doina Precup, Satinder Singh - 1999
443 Decision-Theoretic Planning: Structural Assumptions and Computational Leverage – Craig Boutilier, Thomas Dean, Steve Hanks - 1999
Local defect correction methods for the Bellman equation – Stephan W. E. Pareigis
2 A Hybrid Grid Refinement Scheme for Reinforcement Learning Based on Local Defect Correcting Methods – Stephan Pareigis, Martin Riedmiller - 1997
243 Learning policies for partially observable environments: Scaling up – Michael L. Littman, Anthony R. Cassandra, Leslie Pack Kaelbling - 1995
182 Algorithms for Sequential Decision Making – Michael Lederman Littman - 1996