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Pseudorehearsal in value function approximation

Abstract · Mar 21, 2017 07:09 ·


Arxiv Abstract

  • Vladimir Marochko
  • Leonard Johard
  • Manuel Mazzara

Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole balancing task. We have found that pseudorehearsal seems to assist learning even in such very simple problems, given proper initialization of the rehearsal parameters.

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