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ICCBR
2010
Springer
13 years 8 months ago
Reducing the Memory Footprint of Temporal Difference Learning over Finitely Many States by Using Case-Based Generalization
In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...
Matt Dilts, Héctor Muñoz-Avila
PKDD
2009
Springer
169views Data Mining» more  PKDD 2009»
13 years 11 months ago
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
The goal of approximate policy evaluation is to “best” represent a target value function according to a specific criterion. Temporal difference methods and Bellman residual m...
Jeffrey Johns, Marek Petrik, Sridhar Mahadevan