Assisted-Value Factorization with Latent Interaction in Cooperate Multi-Agent Reinforcement Learning

Assisted-Value Factorization with Latent Interaction in Cooperate Multi-Agent Reinforcement Learning

With the development of value decomposition methods, multi-agent reinforcement learning (MARL) has made significant progress in balancing autonomous decision making with collective cooperation. However, the collaborative dynamics among agents are continuously changing. The current value decompositio...

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Bibliographic Details
Main Authors:	Zhitong Zhao, Ya Zhang, Siying Wang, Yang Zhou, Ruoning Zhang, Wenyu Chen
Format:	Article
Language:	English
Published:	MDPI AG 2025-04-01
Series:	Mathematics
Subjects:	reinforcement learning decentralized partially observable Markov decision process (Dec-POMDP) multi-agent reinforcement learning multi-agent value decomposition
Online Access:	https://www.mdpi.com/2227-7390/13/9/1429
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