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Reinforcement learning via kernel temporal difference. | LitMetric

Reinforcement learning via kernel temporal difference.

Annu Int Conf IEEE Eng Med Biol Soc

Department of Electrical and Computer Engineering, PO Box 116130 NEB 486, Bldg #33, University of Florida, Gainesville, FL 32611, USA.

Published: June 2012

This paper introduces a kernel adaptive filter implemented with stochastic gradient on temporal differences, kernel Temporal Difference (TD)(λ), to estimate the state-action value function in reinforcement learning. The case λ=0 will be studied in this paper. Experimental results show the method's applicability for learning motor state decoding during a center-out reaching task performed by a monkey. The results are compared to the implementation of a time delay neural network (TDNN) trained with backpropagation of the temporal difference error. From the experiments, it is observed that kernel TD(0) allows faster convergence and a better solution than the neural network.

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http://dx.doi.org/10.1109/IEMBS.2011.6091370DOI Listing

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