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Experimental quantum speed-up in reinforcement learning agents
As the field of artificial intelligence advances, the demand for algorithms that can learn quickly and efficiently increases. An important paradigm within artificial intelligence is reinforcement learning [1], where decision-making entities called agents interact with environments and learn by updat...
| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612051/ https://www.ncbi.nlm.nih.gov/pubmed/33692560 http://dx.doi.org/10.1038/s41586-021-03242-7 |