Optimizing agent behavior over long time scales by transporting value
People are able to mentally time travel to distant memories and reflect on the consequences of those past events. Here, the authors show how a mechanism that connects learning from delayed rewards with memory retrieval can enable AI agents to discover links between past events to help decide better...
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| Principais autores: | , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2019-11-01
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| coleção: | Nature Communications |
| Acesso em linha: | https://doi.org/10.1038/s41467-019-13073-w |
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