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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