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FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game 期刊论文
IEEE Transactions on Emerging Topics in Computational Intelligence, 2024, 页码: 1-13
作者:  Guangzheng Hu;  Yuanheng Zhu;  Haoran Li;  Dongbin Zhao
Adobe PDF(2144Kb)  |  收藏  |  浏览/下载：44/8  |  提交时间：2024/06/05
Games  Q-learning  Task analysis  Optimization  Convergence  Training  Nash equilibrium  Multi-agent reinforcement learning  minimax-Q learning  two-team zero-sum Markov games  
Adaptive-weighted deep multi-view clustering with uniform scale representation 期刊论文
NEURAL NETWORKS, 2024, 卷号: 171, 页码: 114-126
作者:  Chen, Rui;  Tang, Yongqiang;  Zhang, Wensheng;  Feng, Wenlong
收藏  |  浏览/下载：89/0  |  提交时间：2024/02/21
Multi-view clustering  Deep clustering  Adaptive-weighted learning  Uniform scale representation