When the dynamical writing of coupled memories with reinforcement learning meets physical bounds
Manipulating binary digits of information (bits) is a prerequisite for reliable memory utilization. The authors present a dynamical framework in which a reinforcement learning agent harnesses the physics of simple multi-bit mechanical models to restore their memory, suggesting new optimal system des...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-02-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-023-01142-y |