Building a computer Mahjong player based on Monte Carlo simulation and opponent models-Reference-Cited by-同舟云学术

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Building a computer Mahjong player based on Monte Carlo simulation and opponent models

Published:2015-08 Issue: Volume: Page:
ISSN:
Container-title:2015 IEEE Conference on Computational Intelligence and Games (CIG)
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Author:

Mizukami Naoki,Tsuruoka Yoshimasa

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7302806/7317656/07317929.pdf?arnumber=7317929

Cited by 30 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MJ-DLVAT: A Deep Learning Value Assessment Technique for Mahjong;2024 IEEE Conference on Games (CoG);2024-08-05

2. Improved learning efficiency of deep Monte-Carlo for complex imperfect-information card games;Applied Soft Computing;2024-06

3. Tjong: A transformer‐based Mahjong AI via hierarchical decision‐making and fan backward;CAAI Transactions on Intelligence Technology;2024-03-21

4. Training a popular Mahjong agent with CNN and self-attention;International Journal of Computing Science and Mathematics;2024

5. Research on improving Mahjong model based on deep reinforcement learning;International Journal of Computing Science and Mathematics;2024

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