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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A Case Study in Hybrid Multi-threading and Hierarchical Reinforcement Learning Approach for Cooperative Multi-agent Systems

2015 Fourteenth Mexican International Conference on Artificial Intelligence (MICAI) ◽

10.1109/micai.2015.20 ◽

2015 ◽

Author(s):

Hiram Ponce ◽

Ricardo Padilla ◽

Alan Davalos ◽

Alvaro Herrasti ◽

Cynthia Pichardo ◽

...

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Multi Agent Systems ◽

Agent Systems ◽

Hierarchical Reinforcement Learning ◽

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Constructive Policy: Reinforcement Learning Approach for Connected Multi-Agent Systems

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) ◽

10.1109/coase.2019.8843223 ◽

2019 ◽

Author(s):

Sayyed Jaffar Ali Raza ◽

Mingjie Lin

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Multi Agent Systems ◽

Agent Systems ◽

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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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Reinforcement Learning Approach for Cooperative Control of Multi-Agent Systems

Proceedings of the 11th International Conference on Agents and Artificial Intelligence ◽

10.5220/0007349000800091 ◽

2019 ◽

Author(s):

Valeria Javalera-Rincon ◽

Vicenc Cayuela ◽

Bernardo Seix ◽

Fernando Orduña-Cabrera

Keyword(s):

Reinforcement Learning ◽

Cooperative Control ◽

Learning Approach ◽

Multi Agent Systems ◽

Agent Systems ◽

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A Reinforcement Learning Approach Using Reliability for Multi-agent Systems

Transactions of the Society of Instrument and Control Engineers ◽

10.9746/sicetr.49.39 ◽

2013 ◽

Vol 49 (1) ◽

pp. 39-47 ◽

Author(s):

Kazuaki YAMADA ◽

Satoru TAKANO

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Multi Agent Systems ◽

Agent Systems ◽

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Input-Output Data-Based Output Antisynchronization Control of Multi-Agent Systems Using Reinforcement Learning Approach

IEEE Transactions on Industrial Informatics ◽

10.1109/tii.2021.3050768 ◽

2021 ◽

pp. 1-1

Author(s):

Zhinan Peng ◽

Yiyi Zhao ◽

Jiangping Hu ◽

Rui Luo ◽

Bijoy Kumar Ghosh ◽

...

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Multi Agent Systems ◽

Input Output ◽

Output Data ◽

Agent Systems ◽

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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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A novel optimal bipartite consensus control scheme for unknown multi-agent systems via model-free reinforcement learning

Applied Mathematics and Computation ◽

10.1016/j.amc.2019.124821 ◽

2020 ◽

Vol 369 ◽

pp. 124821 ◽

Author(s):

Zhinan Peng ◽

Jiangping Hu ◽

Kaibo Shi ◽

Rui Luo ◽

Rui Huang ◽

...

Keyword(s):

Reinforcement Learning ◽

Multi Agent Systems ◽

Consensus Control ◽

Agent Systems ◽

Control Scheme ◽

Multi Agent ◽

Bipartite Consensus

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Formation Control using Simplified Reinforcement Learning for Multi-agent systems with State Delay

10.23919/ccc52363.2021.9549357 ◽

2021 ◽

Author(s):

Wentai Shao ◽

Yutao Chen ◽

Jie Huang

Keyword(s):

Reinforcement Learning ◽

Formation Control ◽

Multi Agent Systems ◽

State Delay ◽

Agent Systems ◽

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Optimized Backstepping Consensus Control Using Reinforcement Learning for a Class of Nonlinear Strict-Feedback-Dynamic Multi-Agent Systems

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2021.3105548 ◽

2021 ◽

pp. 1-13

Author(s):

Guoxing Wen ◽

C. L. Philip Chen

Keyword(s):

Reinforcement Learning ◽

Multi Agent Systems ◽

Consensus Control ◽

Agent Systems ◽

Multi Agent ◽

Strict Feedback

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