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Pseudorehearsal in actor-critic agents with neural network function approximation

Artificial Intelligence 2018-02-20 v2

Abstract

Catastrophic forgetting has a significant negative impact in reinforcement learning. The purpose of this study is to investigate how pseudorehearsal can change performance of an actor-critic agent with neural-network function approximation. We tested agent in a pole balancing task and compared different pseudorehearsal approaches. We have found that pseudorehearsal can assist learning and decrease forgetting.

Keywords

Cite

@article{arxiv.1712.07686,
  title  = {Pseudorehearsal in actor-critic agents with neural network function approximation},
  author = {Vladimir Marochko and Leonard Johard and Manuel Mazzara and Luca Longo},
  journal= {arXiv preprint arXiv:1712.07686},
  year   = {2018}
}
R2 v1 2026-06-22T23:25:10.335Z