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博弈对抗环境中智能策略研究 学位论文
工学博士, 北京: 中国科学院自动化研究所, 2021
Authors:  唐振韬
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深度强化学习  统计前向规划  策略博弈  智能决策  游戏人工智能  
Enhanced Rolling Horizon Evolution Algorithm with Opponent Model Learning 期刊论文
IEEE TRANSACTIONS ON GAMES, 2020, 期号: Early Access, 页码: Early Access
Authors:  Zhentao Tang;  Yuanheng Zhu;  Dongbin Zhao;  Simon M. Lucas
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Rolling horizon evolution  opponent model  reinforcement learning  supervised learning  fighting game  
A Review of Computational Intelligence for StarCraft AI 会议论文
, Bangalore, India, 18-21 Nov. 2018
Authors:  Tang, Zhentao;  Shao, Kun;  Zhu, Yuanheng;  Li, Dong;  Zhao, Dongbin;  Huang, Tingwen
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Reinforcement Learning for Build-Order Production in StarCraft II 会议论文
, Cordoba, Granada, and Seville, Spain, 30 June-6 July 2018
Authors:  Zhentao Tang;  Dongbin Zhao;  Yuanheng Zhu;  Ping Guo
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Visual Scenes Mining for Agent Awareness Module 会议论文
, New York City, NY, USA, 12 - 16 July 2017
Authors:  Ma, Gang;  Tang, Zhentao;  Yang, Xi;  Shi, Zhongzhi;  Yang, Kun
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Agent  Visual Scenes Mining  Abgp-cnn  
ADP with MCTS algorithm for Gomoku 会议论文
, Athens, Greece, 6-9 Dec. 2016
Authors:  Tang Zhentao;  Zhao Dongbin;  Shao Kun;  Lv Le
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深度强化学习进展: 从 AlphaGo 到 AlphaGo Zero 期刊论文
控 制 理 论 与 应 用, 2017, 卷号: 34, 期号: 12, 页码: 1529-1546
Authors:  唐振韬;  邵 坤;  赵冬斌;  朱圆恒
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深度强化学习  AlphaGo Zero  深度学习  强化学习  人工智能  
Move Prediction in Gomoku Using Deep Learning 会议论文
, Wuhan, China, November 11-13, 2016
Authors:  Shao, Kun;  Zhao, Bongbin;  Tang, Zhentao;  Zhu, Yuanheng
Adobe PDF(321Kb)  |  Favorite  |  View/Download:577/358  |  Submit date:2017/12/29
Gomoku  Move Prediction  Deep Learning  Deep Convolutional Network