Antoine Bergerault

Matching multiple experts: on the exploitability of multi-agent imitation learning

Multi-agent imitation learning (MA-IL) aims to learn optimal policies from expert demonstrations in multi-agent interactive domains. Despite existing guarantees on the performance of the extracted policy, characterizations of its distance to a Nash equilibrium are missing for offline MA-IL. In this…