Replay in minds and machines
| Autor: | Lennart Wittkuhn, Samson Chien, Sam Hall-McMaster, Nicolas W. Schuck |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Cognitive science
0303 health sciences Forgetting Brain activity and meditation Mechanism (biology) Computer science Rest Cognitive Neuroscience Hippocampus Variety (cybernetics) 03 medical and health sciences Behavioral Neuroscience 0302 clinical medicine Neuropsychology and Physiological Psychology Generalization (learning) Humans Reinforcement learning Wakefulness Sleep Feature learning 030217 neurology & neurosurgery 030304 developmental biology |
| Zdroj: | Neuroscience & Biobehavioral Reviews |
| ISSN: | 0149-7634 |
| DOI: | 10.1016/j.neubiorev.2021.08.002 |
| Popis: | Experience-related brain activity patterns reactivate during sleep, wakeful rest, and brief pauses from active behavior. In parallel, machine learning research has found that experience replay can lead to substantial performance improvements in artificial agents. Together, these lines of research suggest that replay has a variety of computational benefits for decision-making and learning. Here, we provide an overview of putative computational functions of replay as suggested by machine learning and neuroscientific research. We show that replay can lead to faster learning, less forgetting, reorganization or augmentation of experiences, and support planning and generalization. In addition, we highlight the benefits of reactivating abstracted internal representations rather than veridical memories, and discuss how replay could provide a mechanism to build internal representations that improve learning and decision-making. |
| Databáze: | OpenAIRE |
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