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Shigeng Zhang

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Jul 2026

Learning from success: efficient selective learning methods for multi-agent sparse-reward tasks

This paper proposes effective multi-agent selective learning methods to boost sample-efficient training by learning from successful experiences, and adopts a retrogression-based selection method to identify successful agent trajectories from the team rewards.

Xinning Chen, Xuan Liu, Yanwen Ba et al. · 0 citations