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Zhongxiang Ling

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2025

Multi-Agent Imitation by Learning and Sampling from Factorized Soft Q-Function

This work proposes MAFIS, a novel method that addresses limitations for both online and offline MAIL settings by building upon the single-agent IQ-Learn framework and introducing the value decomposition network to factorize the imitation objective at agent level, thus enabling scalable training for multi-agent systems.

Yichen Li, Zhongxiang Ling, Tao Jiang et al. · 3 citations

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