A Simple, Solid, and Reproducible Baseline for Bridge Bidding AI
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866910490279542784 |
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| author | Kita, Haruka Koyamada, Sotetsu Yamaguchi, Yotaro Ishii, Shin |
| author_facet | Kita, Haruka Koyamada, Sotetsu Yamaguchi, Yotaro Ishii, Shin |
| contents | Contract bridge, a cooperative game characterized by imperfect information and multi-agent dynamics, poses significant challenges and serves as a critical benchmark in artificial intelligence (AI) research. Success in this domain requires agents to effectively cooperate with their partners. This study demonstrates that an appropriate combination of existing methods can perform surprisingly well in bridge bidding against WBridge5, a leading benchmark in the bridge bidding system and a multiple-time World Computer-Bridge Championship winner. Our approach is notably simple, yet it outperforms the current state-of-the-art methodologies in this field. Furthermore, we have made our code and models publicly available as open-source software. This initiative provides a strong starting foundation for future bridge AI research, facilitating the development and verification of new strategies and advancements in the field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_10306 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Simple, Solid, and Reproducible Baseline for Bridge Bidding AI Kita, Haruka Koyamada, Sotetsu Yamaguchi, Yotaro Ishii, Shin Artificial Intelligence Computer Science and Game Theory Machine Learning Contract bridge, a cooperative game characterized by imperfect information and multi-agent dynamics, poses significant challenges and serves as a critical benchmark in artificial intelligence (AI) research. Success in this domain requires agents to effectively cooperate with their partners. This study demonstrates that an appropriate combination of existing methods can perform surprisingly well in bridge bidding against WBridge5, a leading benchmark in the bridge bidding system and a multiple-time World Computer-Bridge Championship winner. Our approach is notably simple, yet it outperforms the current state-of-the-art methodologies in this field. Furthermore, we have made our code and models publicly available as open-source software. This initiative provides a strong starting foundation for future bridge AI research, facilitating the development and verification of new strategies and advancements in the field. |
| title | A Simple, Solid, and Reproducible Baseline for Bridge Bidding AI |
| topic | Artificial Intelligence Computer Science and Game Theory Machine Learning |
| url | https://arxiv.org/abs/2406.10306 |