Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem

Authors:
Verena Heidrich-Meisner;Christian Igel
Affiliations:
Institut für Neuroinformatik, Ruhr-Universität Bochum, Germany;Institut für Neuroinformatik, Ruhr-Universität Bochum, Germany
Venue:
Recent Advances in Reinforcement Learning
Year:
2008

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Abstract

Two variable metric reinforcement learning methods, the natural actor-critic algorithm and the covariance matrix adaptation evolution strategy, are compared on a conceptual level and analysed experimentally on the mountain car benchmark task with and without noise.