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-...
In this project, we will explore whether children and adults can learn non-intuitive physicalforces, particularly those that violate our core knowledge about the physical world, and whether thislearning varies as a function of age. For example, can children and adults who are exploring andinteracting with VR worlds learn that...
In this project, we will explore whether children and adults can learn non-intuitive physical