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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591094/ https://www.ncbi.nlm.nih.gov/pubmed/33057329 http://dx.doi.org/10.1371/journal.pcbi.1008317 |