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Reward-predictive representations generalize across tasks in reinforcement learning
In computer science, reinforcement learning is a powerful framework with which artificial agents can learn to maximize their performance for any given Markov decision process (MDP). Advances over the last decade, in combination with deep neural networks, have enjoyed performance advantages over huma...
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| Publicado no: | PLoS Comput Biol |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7591094/ https://ncbi.nlm.nih.gov/pubmed/33057329 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1008317 |
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