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ICCBR
2010
Springer
15 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
NIPS
1993
15 years 5 months ago
Temporal Difference Learning of Position Evaluation in the Game of Go
The game of Go has a high branching factor that defeats the tree search approach used in computer chess, and long-range spatiotemporal interactions that make position evaluation e...
Nicol N. Schraudolph, Peter Dayan, Terrence J. Sej...
AR
2002
157views more  AR 2002»
15 years 4 months ago
Acquiring state from control dynamics to learn grasping policies for robot hands
Abstract--A prominent emerging theory of sensorimotor development in biological systems proposes that control knowledge is encoded in the dynamics of physical interaction with the ...
Roderic A. Grupen, Jefferson A. Coelho Jr.
ICML
1994
IEEE
15 years 8 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager
ECLIPSE
2007
ACM
15 years 8 months ago
Predicting buggy changes inside an integrated development environment
We present a tool that predicts whether the software under development inside an IDE has a bug. An IDE plugin performs this prediction, using the Change Classification technique t...
Janaki T. Madhavan, E. James Whitehead Jr.