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

摘要

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.