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 |
| _version_ | 1811171735030988800 |
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| author | Théo Jules Laura Michel Adèle Douin Frédéric Lechenault |
| author_facet | Théo Jules Laura Michel Adèle Douin Frédéric Lechenault |
| author_sort | Théo Jules |
| collection | DOAJ |
| description | 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 designs. |
| first_indexed | 2024-04-10T17:18:58Z |
| format | Article |
| id | doaj.art-fdfd4e5eadb949498017a14a864d308c |
| institution | Directory Open Access Journal |
| issn | 2399-3650 |
| language | English |
| last_indexed | 2024-04-10T17:18:58Z |
| publishDate | 2023-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Physics |
| spelling | doaj.art-fdfd4e5eadb949498017a14a864d308c2023-02-05T12:15:04ZengNature PortfolioCommunications Physics2399-36502023-02-01611810.1038/s42005-023-01142-yWhen the dynamical writing of coupled memories with reinforcement learning meets physical boundsThéo Jules0Laura Michel1Adèle Douin2Frédéric Lechenault3Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv UniversityLaboratoire de Physique de l’École Normale Supérieure, ENS, PSL Research University, CNRS, Sorbonne University, Université Paris DiderotLaboratoire de Physique de l’École Normale Supérieure, ENS, PSL Research University, CNRS, Sorbonne University, Université Paris DiderotLaboratoire de Physique de l’École Normale Supérieure, ENS, PSL Research University, CNRS, Sorbonne University, Université Paris DiderotManipulating 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 designs.https://doi.org/10.1038/s42005-023-01142-y |
| spellingShingle | Théo Jules Laura Michel Adèle Douin Frédéric Lechenault When the dynamical writing of coupled memories with reinforcement learning meets physical bounds Communications Physics |
| title | When the dynamical writing of coupled memories with reinforcement learning meets physical bounds |
| title_full | When the dynamical writing of coupled memories with reinforcement learning meets physical bounds |
| title_fullStr | When the dynamical writing of coupled memories with reinforcement learning meets physical bounds |
| title_full_unstemmed | When the dynamical writing of coupled memories with reinforcement learning meets physical bounds |
| title_short | When the dynamical writing of coupled memories with reinforcement learning meets physical bounds |
| title_sort | when the dynamical writing of coupled memories with reinforcement learning meets physical bounds |
| url | https://doi.org/10.1038/s42005-023-01142-y |
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