no code implementations • 22 Feb 2023 • Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan
In this paper, we propose a method of learning representations that are instead equivariant to data augmentations.
1 code implementation • 16 Aug 2022 • Nishanth Kumar, Willie McClinton, Rohan Chitnis, Tom Silver, Tomás Lozano-Pérez, Leslie Pack Kaelbling
Bilevel planning, in which a high-level search over an abstraction of an environment is used to guide low-level decision-making, is an effective approach to solving long-horizon tasks in continuous state and action spaces.
1 code implementation • 17 Mar 2022 • Tom Silver, Rohan Chitnis, Nishanth Kumar, Willie McClinton, Tomas Lozano-Perez, Leslie Pack Kaelbling, Joshua Tenenbaum
Our key idea is to learn predicates by optimizing a surrogate objective that is tractable but faithful to our real efficient-planning objective.
no code implementations • 12 Aug 2021 • Willie McClinton, Andrew Levy, George Konidaris
Sparse rewards and long time horizons remain challenging for reinforcement learning algorithms.