research
∙
05/24/2023
Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Animals have evolved various agile locomotion strategies, such as sprint...
share
research
∙
05/02/2023
Get Back Here: Robust Imitation by Return-to-Distribution Planning
We consider the Imitation Learning (IL) setup where expert data are not ...
research
∙
02/08/2023
Investigating the role of model-based learning in exploration and transfer
State of the art reinforcement learning has enabled training agents on t...
research
∙
11/16/2022
Learning Reward Functions for Robotic Manipulation by Observing Humans
Observing a human demonstrator manipulate objects provides a rich, scala...
research
∙
11/07/2022
C3PO: Learning to Achieve Arbitrary Goals via Massively Entropic Pretraining
Given a particular embodiment, we propose a novel method (C3PO) that lea...
research
∙
09/29/2021
Learning Dynamics Models for Model Predictive Agents
Model-Based Reinforcement Learning involves learning a dynamics model fr...
research
∙
06/15/2021
Residual Reinforcement Learning from Demonstrations
Residual reinforcement learning (RL) has been proposed as a way to solve...
research
∙
11/14/2020
A Geometric Perspective on Self-Supervised Policy Adaptation
One of the most challenging aspects of real-world reinforcement learning...
research
∙
08/12/2020
Model-Based Offline Planning
Offline learning is a key part of making reinforcement learning (RL) use...
research
∙
06/24/2020
RL Unplugged: Benchmarks for Offline Reinforcement Learning
Offline methods for reinforcement learning have the potential to help br...
research
∙
03/24/2020
An empirical investigation of the challenges of real-world reinforcement learning
Reinforcement learning (RL) has proven its worth in a series of artifici...
research
∙
10/20/2019
Differentiable Deep Clustering with Cluster Size Constraints
Clustering is a fundamental unsupervised learning approach. Many cluster...
research
∙
05/30/2019
Deep multi-class learning from label proportions
We propose a learning algorithm capable of learning from label proportio...
research
∙
04/29/2019
Challenges of Real-World Reinforcement Learning
Reinforcement learning (RL) has proven its worth in a series of artifici...
research
∙
04/12/2017
Deep Q-learning from Demonstrations
Deep reinforcement learning (RL) has achieved several high profile succe...
research
∙
12/28/2016
The Predictron: End-To-End Learning and Planning
One of the key challenges of artificial intelligence is to learn models ...
research
∙
12/24/2015
Deep Reinforcement Learning in Large Discrete Action Spaces
Being able to reason in an environment with a large number of discrete a...
research
∙
12/03/2015
Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions
Many real-world problems come with action spaces represented as feature ...
research
∙
12/20/2013
Sequentially Generated Instance-Dependent Image Representations for Classification
In this paper, we investigate a new framework for image classification t...
research
∙
02/29/2012
Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization
The use of Reinforcement Learning in real-world scenarios is strongly li...
research
∙
08/29/2011
Datum-Wise Classification: A Sequential Approach to Sparsity
We propose a novel classification technique whose aim is to select an ap...
research
∙
07/07/2011