A survey on applications of reinforcement learning in spatial resource allocation
Abstract The challenge of spatial resource allocation is pervasive across various domains such as transportation, industry, and daily life. As the scale of real-world issues continues to expand and demands for real-time solutions increase, traditional algorithms face significant computational pressu...
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| Autori principali: | , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer
2024-06-01
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| Serie: | Computational Urban Science |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/s43762-024-00127-z |
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