Alison Gopnik

Lynch et al. 2019 introduced “Play-LMP”, a self supervised method that learns to organize play behaviors in a latent space, then reuse them at test time to achieve specific goals. Combining self-supervised control with a diverse play dataset shifts the focus of skill learning from a narrow and discrete set of tasks to the full continuum of behaviors available in an environment. They found that this combination generalizes well empirically—after self-supervising on unlabeled play, their method substantially outperforms individual expert-trained policies on 18 difficult user-...