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Learning and forgetting using reinforced Bayesian change detection
Agents living in volatile environments must be able to detect changes in contingencies while refraining to adapt to unexpected events that are caused by noise. In Reinforcement Learning (RL) frameworks, this requires learning rates that adapt to past reliability of the model. The observation that be...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6488101/ https://www.ncbi.nlm.nih.gov/pubmed/30995214 http://dx.doi.org/10.1371/journal.pcbi.1006713 |