Reinforcement learning for collective multi-agent decision making

In this thesis, we study reinforcement learning algorithms to collectively optimize decentralized policy in a large population of autonomous agents. We notice one of the main bottlenecks in large multi-agent system is the size of the joint trajectory of agents which quickly increases with the number...

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Bibliographic Details
Main Author: NGUYEN, Duc Thien
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
Subjects:
Online Access:https://ink.library.smu.edu.sg/etd_coll/162
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1162&context=etd_coll
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Institution: Singapore Management University
Language: English