Reinforcement learning-based tuning algorithm applied to fuzzy identification

Authors:
Mariela Cerrada;Jose Aguilar;André Titli
Affiliations:
Control Systems Department-CEMISID, Universidad de Los Andes, Mérida, Venezuela;Control Systems Department-CEMISID, Universidad de Los Andes, Mérida, Venezuela;DISCO Group, LAAS-CNRS, Toulouse cedex 4, France
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

Citing 8
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Abstract

In on-line applications, reinforcement learning based algorithms allow to take into account the environment information in order to propose an action policy for the overall optimization objectives. In this work, it is presented a learning algorithm based on reinforcement learning and temporal differences allowing the on-line parameters adjustment for identification tasks. As a consequence, the reinforcement signal is generically defined in order to minimize the temporal difference.