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Optimal Policy of Multiplayer Poker via Actor-Critic Reinforcement Learning
Poker has been considered a challenging problem in both artificial intelligence and game theory because poker is characterized by imperfect information and uncertainty, which are similar to many realistic problems like auctioning, pricing, cyber security, and operations. However, it is not clear tha...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222241/ https://www.ncbi.nlm.nih.gov/pubmed/35741495 http://dx.doi.org/10.3390/e24060774 |