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浏览/检索结果:
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Boosting On-Policy Actor-Critic With Shallow Updates in Critic
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 页码: 10
作者:
Li, Luntong
;
Zhu, Yuanheng
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2024/07/03
Artificial neural networks
Vectors
Task analysis
Training
Representation learning
Approximation algorithms
Optimization
Actor-critic
deep reinforcement learning (DRL)
proximal policy optimization (PPO)
shallow reinforcement learning (SRL)
Driving Control with Deep and Reinforcement Learning in The Open Racing Car Simulator
会议论文
, Siem Reap, Cambodia, 2018, 12, 13-16
作者:
Yuanheng Zhu
;
Dongbin Zhao
Adobe PDF(697Kb)
  |  
收藏
  |  
浏览/下载:49/21
  |  
提交时间:2024/06/05
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:55/12
  |  
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
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:66/5
  |  
提交时间:2023/11/16
Large-scale multiagent
neighboring communication
reinforcement learning (RL)
variational information flow
Optimal Pedestrian Evacuation in Building with Consecutive Differential Dynamic Programming
会议论文
, Budapest, Hungary, 2019-7-14
作者:
Zhu YH(朱圆恒)
;
Haibo He
;
Dongbin Zhao
;
Zhongsheng Hou
Adobe PDF(679Kb)
  |  
收藏
  |  
浏览/下载:78/37
  |  
提交时间:2023/05/22
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:262/16
  |  
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
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:299/39
  |  
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:275/13
  |  
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)
Decentralized Event-Driven Constrained Control Using Adaptive Critic Designs
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:
Yang, Xiong
;
Zhu, Yuanheng
;
Dong, Na
;
Wei, Qinglai
Adobe PDF(1578Kb)
  |  
收藏
  |  
浏览/下载:249/17
  |  
提交时间:2022/01/27
Adaptive critic designs (ACDs)
adaptive dynamic programming (ADP)
decentralized event-driven control
input constraint
reinforcement learning (RL)
Missile guidance with assisted deep reinforcement learning for head-on interception of maneuvering target
期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2021, 页码: 12
作者:
Li, Weifan
;
Zhu, Yuanheng
;
Zhao, Dongbin
Adobe PDF(1431Kb)
  |  
收藏
  |  
浏览/下载:337/64
  |  
提交时间:2021/12/28
Reinforcement learning
Missile guidance
Auxiliary learning
Self-imitation learning