Constrained multiagent reinforcement learning for large agent population

Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large...

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Bibliographic Details
Main Authors: LING, Jiajing, SINGH, Arambam James, NGUYEN, Duc Thien, KUMAR, Akshat
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2023
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Online Access:https://ink.library.smu.edu.sg/sis_research/8091
https://ink.library.smu.edu.sg/context/sis_research/article/9094/viewcontent/978_3_031_26412_2_12_pv.pdf
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Institution: Singapore Management University
Language: English

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