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Balancing Exploration and Exploitation in Self-imitation Learning

Sparse reward tasks are always challenging in reinforcement learning. Learning such tasks requires both efficient exploitation and exploration to reduce the sample complexity. One line of research called self-imitation learning is recently proposed, which encourages the agent to do more exploitation...

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Pubblicato in:Advances in Knowledge Discovery and Data Mining
Autori principali: Kang, Chun-Yao, Chen, Ming-Syan
Natura: Artigo
Lingua:Inglês
Pubblicazione: 2020
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7206262/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47436-2_21
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