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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書目詳細資料
Main Authors:	SINGH, Arambam James, KUMAR, Akshat
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2021
主題:	Reinforcement learning Multiagent systems Databases and Information Systems
在線閱讀:	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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