Search Results for author: Willie McClinton

Found 5 papers, 2 papers with code

Practice Makes Perfect: Planning to Learn Skill Parameter Policies

no code implementations22 Feb 2024 Nishanth Kumar, Tom Silver, Willie McClinton, Linfeng Zhao, Stephen Proulx, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Jennifer Barry

We consider a setting where a robot is initially equipped with (1) a library of parameterized skills, (2) an AI planner for sequencing together the skills given a goal, and (3) a very general prior distribution for selecting skill parameters.

Active Learning Decision Making

Steerable Equivariant Representation Learning

no code implementations22 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.

Image Retrieval object-detection +5

Learning Efficient Abstract Planning Models that Choose What to Predict

1 code implementation16 Aug 2022 Nishanth Kumar, Willie McClinton, Rohan Chitnis, Tom Silver, Tomás Lozano-Pérez, Leslie Pack Kaelbling

An effective approach to solving long-horizon tasks in robotics domains with continuous state and action spaces is bilevel planning, wherein a high-level search over an abstraction of an environment is used to guide low-level decision-making.

Decision Making Operator learning

Predicate Invention for Bilevel Planning

1 code implementation17 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.

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