In the first part of the talk, I will introduce Multi-agent Generative Adversarial Imitation Learning, a new framework for multi-agent imitation learning for general Markov games, where we build upon a generalized notion of inverse reinforcement learning. Multi-agent settings are challenging due to the existence of multiple (Nash) equilibria and non-stationary environments. Our method can […]