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Map-based experience replay: a memory-efficient solution to catastrophic forgetting in reinforcement learning
Deep reinforcement learning (RL) agents often suffer from catastrophic forgetting, forgetting previously found solutions in parts of the input space when training new data. Replay memories are a common solution to the problem by decorrelating and shuffling old and new training samples. They naively...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333526/ https://www.ncbi.nlm.nih.gov/pubmed/37440981 http://dx.doi.org/10.3389/fnbot.2023.1127642 |