Approximate difference rewards for scalable multigent reinforcement learning

Approximate difference rewards for scalable multigent reinforcement learning

We address the problem of multiagent credit assignment in a large scale multiagent system. Difference rewards (DRs) are an effective tool to tackle this problem, but their exact computation is known to be challenging even for small number of agents. We propose a scalable method to compute difference...

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Bibliographic Details
Main Authors:	SINGH, Arambam James, KUMAR, Akshat
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 2021
Subjects:	Reinforcement learning Multiagent systems Databases and Information Systems
Online Access:	https://ink.library.smu.edu.sg/sis_research/6901 https://ink.library.smu.edu.sg/context/sis_research/article/7904/viewcontent/Approximate_Difference_Rewards_for_Scalable_Multiagent.pdf
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Institution:	Singapore Management University
Language:	English

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