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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：32/4  |  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  
Deep Reinforcement Learning-Based Driving Policy at Intersections Utilizing Lane Graph Networks 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2024, 页码: 1 - 16
作者:  Liu, Yuqi;  Zhang, Qichao;  Gao, Yinfeng;  Zhao, Dongbin
Adobe PDF(22863Kb)  |  收藏  |  浏览/下载：30/8  |  提交时间：2024/06/03
Reinforcement Learning  Autonomous Driving  Intersection Navigating  
Multi-task safe reinforcement learning for navigating intersections in dense traffic 期刊论文
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2023, 卷号: 360, 期号: 17, 页码: 13737-13760
作者:  Liu, Yuqi;  Gao, Yinfeng;  Zhang, Qichao;  Ding, Dawei;  Zhao, Dongbin
Adobe PDF(3095Kb)  |  收藏  |  浏览/下载：74/13  |  提交时间：2024/02/22
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
Adobe PDF(2469Kb)  |  收藏  |  浏览/下载：61/3  |  提交时间：2023/11/16
Large-scale multiagent  neighboring communication  reinforcement learning (RL)  variational information flow  
Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 3, 页码: 1228-1241
作者:  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(2838Kb)  |  收藏  |  浏览/下载：239/8  |  提交时间：2022/06/10
Games  Nash equilibrium  Mathematical model  Markov processes  Convergence  Dynamic programming  Training  Deep reinforcement learning (DRL)  generalized policy iteration (GPI)  Markov game (MG)  Nash equilibrium  Q network  zero sum  
Boost 3-D Object Detection via Point Clouds Segmentation and Fused 3-D GIoU-L-1 Loss 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 2, 页码: 762-773
作者:  Chen, Yaran;  Li, Haoran;  Gao, Ruiyuan;  Zhao, Dongbin
Adobe PDF(2082Kb)  |  收藏  |  浏览/下载：289/67  |  提交时间：2022/03/17
3-D object detection  generalized Intersection of Union (GIoU) loss  segmentation  
UNMAS: Multiagent Reinforcement Learning for Unshaped Cooperative Scenarios 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 12
作者:  Chai, Jiajun;  Li, Weifan;  Zhu, Yuanheng;  Zhao, Dongbin;  Ma, Zhe;  Sun, Kewu;  Ding, Jishiyu
Adobe PDF(3402Kb)  |  收藏  |  浏览/下载：280/33  |  提交时间：2022/01/27
Multi-agent systems  Training  Task analysis  Reinforcement learning  Sun  Learning systems  Semantics  Centralized training with decentralized execution (CTDE)  multiagent  reinforcement learning  StarCraft II  
Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Hu, Guangzheng;  Zhu, Yuanheng;  Zhao, Dongbin;  Zhao, Mengchen;  Hao, Jianye
Adobe PDF(4187Kb)  |  收藏  |  浏览/下载：255/10  |  提交时间：2022/01/27
Bandwidth  Protocols  Reinforcement learning  Task analysis  Optimization  Communication networks  Multi-agent systems  Event trigger  limited bandwidth  multi-agent communication  multi-agent reinforcement learning (MARL)  
Optimal Feedback Control of Pedestrian Flow in Heterogeneous Corridors 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 卷号: 18, 期号: 3, 页码: 1097-1108
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo
Adobe PDF(2666Kb)  |  收藏  |  浏览/下载：228/14  |  提交时间：2021/08/15
Microscopy  Feedback control  Mathematical model  Data models  Dynamic programming  Psychology  Computational modeling  Adaptive dynamic programming (ADP)  heterogeneous corridors  macroscopic pedestrian dynamics  optimal feedback control  pedestrian flow  
Enhanced Rolling Horizon Evolution Algorithm With Opponent Model Learning: Results for the Fighting Game AI Competition 期刊论文
IEEE TRANSACTIONS ON GAMES, 2023, 卷号: 5, 期号: 1, 页码: 5 - 15
作者:  Zhentao Tang;  Yuanheng Zhu;  Dongbin Zhao;  Simon M. Lucas
Adobe PDF(7686Kb)  |  收藏  |  浏览/下载：338/70  |  提交时间：2021/07/05
Rolling horizon evolution  opponent model  reinforcement learning  supervised learning  fighting game