A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.2021 ◽

2020 ◽

Vol 53 (2) ◽

pp. 1549-1554

Author(s):

Wesley Suttle ◽

Zhuoran Yang ◽

Kaiqing Zhang ◽

Zhaoran Wang ◽

Tamer Başar ◽

...

Keyword(s):

Reinforcement Learning ◽

Policy Actor ◽

Multi Agent ◽

Distributed Reinforcement

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Toward Resilient Multi-Agent Actor-Critic Algorithms for Distributed Reinforcement Learning

2020 American Control Conference (ACC) ◽

10.23919/acc45564.2020.9147381 ◽

2020 ◽

Author(s):

Yixuan Lin ◽

Shripad Gade ◽

Romeil Sandhu ◽

Ji Liu

Keyword(s):

Reinforcement Learning ◽

Multi Agent ◽

Distributed Reinforcement

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Distributed reinforcement learning in multi-agent networks

2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) ◽

10.1109/camsap.2013.6714066 ◽

2013 ◽

Author(s):

Soummya Kar ◽

Jose M. F. Moura ◽

H. Vincent Poor

Keyword(s):

Reinforcement Learning ◽

Multi Agent ◽

Agent Networks ◽

Distributed Reinforcement

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Multi-Agent Systems on Sensor Networks: A Distributed Reinforcement Learning Approach

2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing ◽

10.1109/issnip.2005.1595616 ◽

2005 ◽

Author(s):

Chen-Khong Tham ◽

J.-C. Renaud

Keyword(s):

Reinforcement Learning ◽

Sensor Networks ◽

Learning Approach ◽

Multi Agent Systems ◽

Agent Systems ◽

Multi Agent ◽

Distributed Reinforcement

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Cooperative Multi-Agent Systems Using Distributed Reinforcement Learning Techniques

Procedia Computer Science ◽

10.1016/j.procs.2018.07.286 ◽

2018 ◽

Vol 126 ◽

pp. 517-526 ◽

Author(s):

Wiem Zemzem ◽

Moncef Tagina

Keyword(s):

Reinforcement Learning ◽

Multi Agent Systems ◽

Agent Systems ◽

Learning Techniques ◽

Multi Agent ◽

Distributed Reinforcement

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A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning*

2019 IEEE 58th Conference on Decision and Control (CDC) ◽

10.1109/cdc40024.2019.9029257 ◽

2019 ◽

Author(s):

Yixuan Lin ◽

Kaiqing Zhang ◽

Zhuoran Yang ◽

Zhaoran Wang ◽

Tamer Basar ◽

...

Keyword(s):

Reinforcement Learning ◽

Multi Agent ◽

Distributed Reinforcement

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Distributed Reinforcement Learning in Multi-agent Decision Systems

Lecture Notes in Computer Science - Progress in Artificial Intelligence — IBERAMIA 98 ◽

10.1007/3-540-49795-1_13 ◽

1998 ◽

pp. 148-159 ◽

Author(s):

J. Ignacio Giráldez ◽

Daniel Borrajo

Keyword(s):

Reinforcement Learning ◽

Decision Systems ◽

Multi Agent ◽

Distributed Reinforcement

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A Multi-agent-based voltage control in power systems using distributed reinforcement learning

10.1177/0037549710367904 ◽

2010 ◽

Vol 87 (7) ◽

pp. 581-599 ◽

Author(s):

M.Reza Tousi ◽

S. Hossein Hosseinian ◽

M. Bagher Menhaj

Keyword(s):

Reinforcement Learning ◽

Power Systems ◽

Voltage Control ◽

Agent Based ◽

Multi Agent ◽

Distributed Reinforcement

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Multi-Agent Deep Reinforcement Learning for Decentralized Cooperative Traffic Signal Control

10.1061/9780784483053.039 ◽

2020 ◽

Author(s):

Yang Zhao ◽

Jian-Ming Hu ◽

Ming-Yang Gao ◽

Zuo Zhang

Keyword(s):

Reinforcement Learning ◽

Traffic Signal ◽

Signal Control ◽

Traffic Signal Control ◽

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Output feedback reinforcement learning based optimal output synchronisation of heterogeneous discrete-time multi-agent systems

IET Control Theory and Applications ◽

10.1049/iet-cta.2018.6266 ◽

2019 ◽

Vol 13 (17) ◽

pp. 2866-2876

Author(s):

Syed Ali Asad Rizvi ◽

Zongli Lin

Keyword(s):

Reinforcement Learning ◽

Discrete Time ◽

Output Feedback ◽

Multi Agent Systems ◽

Agent Systems ◽

Optimal Output ◽

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Distributed Reinforcement Learning for Multi-robot Decentralized Collective Construction

Distributed Autonomous Robotic Systems - Springer Proceedings in Advanced Robotics ◽

10.1007/978-3-030-05816-6_3 ◽

2019 ◽

pp. 35-49 ◽

Author(s):

Guillaume Sartoretti ◽

Yue Wu ◽

William Paivine ◽

T. K. Satish Kumar ◽

Sven Koenig ◽

...

Keyword(s):

Reinforcement Learning ◽

Collective Construction ◽

Distributed Reinforcement ◽

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