Distributed Multi-Agent Reinforcement Learning by Actor-Critic Method

被引：10
|
作者：
Heredia, Paulo C. [1 ]
Mou, Shaoshuai [1 ]
机构：
[1] Purdue Univ, W Lafayette, IN 47906 USA
来源：
IFAC PAPERSONLINE | 2019年 / 52卷 / 20期
关键词：
D O I：
10.1016/j.ifacol.2019.12.182
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We investigate the problem of multi-agent reinforcement learning, in which each agent only has access to its local reward and can only communicate with its nearby neighbors. A distributed algorithm based on actor-critic method has been developed to enable all agents to cooperatively learn a control policy that maximizes the global objective function. Simulations are also provided to validate the proposed algorithm. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：363 / 368
页数：6
相关论文
共 50 条
  • [21] Entropy regularized actor-critic based multi-agent deep reinforcement learning for stochastic games
    Hao, Dong
    Zhang, Dongcheng
    Shi, Qi
    Li, Kai
    [J]. INFORMATION SCIENCES, 2022, 617 : 17 - 40
  • [22] Entropy regularized actor-critic based multi-agent deep reinforcement learning for stochastic games
    Hao, Dong
    Zhang, Dongcheng
    Shi, Qi
    Li, Kai
    [J]. Information Sciences, 2022, 617 : 17 - 40
  • [23] Multi-actor mechanism for actor-critic reinforcement learning
    Li, Lin
    Li, Yuze
    Wei, Wei
    Zhang, Yujia
    Liang, Jiye
    [J]. INFORMATION SCIENCES, 2023, 647
  • [24] Actor-Attention-Critic for Multi-Agent Reinforcement Learning
    Iqbal, Shariq
    Sha, Fei
    [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 97, 2019, 97
  • [25] B -Level Actor-Critic for Multi-Agent Coordination
    Zhang, Haifeng
    Chen, Weizhe
    Huang, Zeren
    Li, Minne
    Yang, Yaodong
    Zhang, Weinan
    Wang, Jun
    [J]. THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2020, 34 : 7325 - 7332
  • [26] Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
    Chen, Dingyang
    Zhang, Qi
    [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 202, 2023, 202
  • [27] UAV Assisted Cooperative Caching on Network Edge Using Multi-Agent Actor-Critic Reinforcement Learning
    Araf, Sadman
    Saha, Adittya Soukarjya
    Kazi, Sadia Hamid
    Tran, Nguyen H. H.
    Alam, Md. Golam Rabiul
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (02) : 2322 - 2337
  • [28] Divergence-Regularized Multi-Agent Actor-Critic
    Su, Kefan
    Lu, Zongqing
    [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162, 2022,
  • [29] AHAC: Actor Hierarchical Attention Critic for Multi-Agent Reinforcement Learning
    Wang, Yajie
    Shi, Dianxi
    Xue, Chao
    Jiang, Hao
    Wang, Gongju
    Gong, Peng
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2020, : 3013 - 3020
  • [30] Swarm Reinforcement Learning Method Based on an Actor-Critic Method
    Iima, Hitoshi
    Kuroe, Yasuaki
    [J]. SIMULATED EVOLUTION AND LEARNING, 2010, 6457 : 279 - 288
12345