Coordinated Multi-Agent Imitation Learning [article]

Hoang M. Le, Yisong Yue, Peter Carr, Patrick Lucey
2018 arXiv   pre-print
We study the problem of imitation learning from demonstrations of multiple coordinating agents. One key challenge in this setting is that learning a good model of coordination can be difficult, since coordination is often implicit in the demonstrations and must be inferred as a latent variable. We propose a joint approach that simultaneously learns a latent coordination model along with the individual policies. In particular, our method integrates unsupervised structure learning with
more » ... l imitation learning. We illustrate the power of our approach on a difficult problem of learning multiple policies for fine-grained behavior modeling in team sports, where different players occupy different roles in the coordinated team strategy. We show that having a coordination model to infer the roles of players yields substantially improved imitation loss compared to conventional baselines.
arXiv:1703.03121v2 fatcat:ie24xw27c5ghrjc2hhka4c5are