Pseudorehearsal in actor-critic agents with neural network function approximation
December 20, 2017 Β· Declared Dead Β· π International Conference on Advanced Information Networking and Applications
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Authors
Vladimir Marochko, Leonard Johard, Manuel Mazzara, Luca Longo
arXiv ID
1712.07686
Category
cs.AI: Artificial Intelligence
Citations
2
Venue
International Conference on Advanced Information Networking and Applications
Last Checked
4 months ago
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.
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