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浏览/检索结果: 共5条，第1-5条 帮助 限定条件 发表日期：2023     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Multiagent-Reinforcement-Learning-Based Stable Path Tracking Control for a Bionic Robotic Fish With Reaction Wheel 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2023, 卷号: 70, 期号: 12, 页码: 12670-12679 作者:  Qiu, Changlin;  Wu, Zhengxing;  Wang, Jian;  Tan, Min;  Yu, Junzhi 收藏  |  浏览/下载：6/0  |  提交时间：2023/11/17 Multiagent reinforcement learning (MARL)  path tracking control  reaction wheel  robotic fish  underwater robot   Peer Incentive Reinforcement Learning for Cooperative Multiagent Games 期刊论文 IEEE TRANSACTIONS ON GAMES, 2023, 卷号: 15, 期号: 4, 页码: 623-636 作者:  Zhang, Tianle;  Liu, Zhen;  Pu, Zhiqiang;  Yi, Jianqiang 收藏  |  浏览/下载：1/0  |  提交时间：2024/02/22 Cooperative multiagent games  intrinsic reward  multiagent reinforcement learning (MARL)  Starcraft II Micromanagement   NVIF: Neighboring Variational Information Flow for Cooperative Large-Scale Multiagent Reinforcement Learning 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13 作者:  Chai, Jiajun;  Zhu, Yuanheng;  Zhao, Dongbin 收藏  |  浏览/下载：3/0  |  提交时间：2023/11/16 Large-scale multiagent  neighboring communication  reinforcement learning (RL)  variational information flow   Multiexperience-Assisted Efficient Multiagent Reinforcement Learning 期刊论文 IEEE Transactions on Neural Networks and Learning Systems, 2023, 页码: 1-15 作者:  Zhang TL(张天乐);  Liu Z(刘振);  Yi JQ(易建强);  Wu SG(吴士广);  Pu ZQ(蒲志强) 收藏  |  浏览/下载：14/0  |  提交时间：2023/06/02 Network-Wide Traffic Signal Control Based on MARL With Hierarchical Nash-Stackelberg Game Model 期刊论文 IEEE ACCESS, 2023, 卷号: 11, 页码: 145085-145100 作者:  Shen, Hui;  Zhao, Hongxia;  Zhang, Zundong;  Yang, Xun;  Song, Yutong 收藏  |  浏览/下载：0/0  |  提交时间：2024/02/22 Games  Roads  Approximation algorithms  Q-learning  Multi-agent systems  Process control  Optimization  Reinforcement learning  Traffic control  Network-wide traffic signal control  hierarchical game model  multi-agent reinforcement learning