arXiv cs.LG
· Papers
Multi-agent imitation learning with function approximation: Linear Markov games and beyond
arXiv:2602.22810v2 Announce Type: replace Abstract: In this work, we present the first theoretical analysis of multi-agent imitation learning (MAIL) in linear Markov games where both the transition dynamics and each agent's reward function are linear in some given features. We demonstrate that by leveraging this struct