research
∙
06/15/2023
Granger-Causal Hierarchical Skill Discovery
Reinforcement Learning (RL) has shown promising results learning policie...
share
research
∙
02/16/2023
Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods
It is well known that Reinforcement Learning (RL) can be formulated as a...
research
∙
01/24/2023
Language-guided Task Adaptation for Imitation Learning
We introduce a novel setting, wherein an agent needs to learn a task fro...
research
∙
11/01/2022
Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots
Humans use audio signals in the form of spoken language or verbal reacti...
research
∙
06/05/2022
Models of human preference for learning reward functions
The utility of reinforcement learning is limited by the alignment of rew...
research
∙
06/01/2022
Know Your Boundaries: The Necessity of Explicit Behavioral Cloning in Offline RL
We introduce an offline reinforcement learning (RL) algorithm that expli...
research
∙
02/07/2022
A Ranking Game for Imitation Learning
We propose a new framework for imitation learning - treating imitation a...
research
∙
11/06/2021
SOPE: Spectrum of Off-Policy Estimators
Many sequential decision making problems are high-stakes and require off...
research
∙
10/05/2021
You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL
The goal of offline reinforcement learning (RL) is to find an optimal po...
research
∙
08/12/2021
Distributional Depth-Based Estimation of Object Articulation Models
We propose a method that efficiently learns distributions over articulat...
research
∙
06/30/2021
Robust Generative Adversarial Imitation Learning via Local Lipschitzness
We explore methodologies to improve the robustness of generative adversa...
research
∙
06/05/2021
Zero-shot Task Adaptation using Natural Language
Imitation learning and instruction-following are two common approaches t...
research
∙
05/27/2021
Adversarial Intrinsic Motivation for Reinforcement Learning
Learning with an objective to minimize the mismatch with a reference dis...
research
∙
04/26/2021
Universal Off-Policy Evaluation
When faced with sequential decision-making problems, it is often useful ...
research
∙
03/08/2021
Self-Supervised Online Reward Shaping in Sparse-Reward Environments
We propose a novel reinforcement learning framework that performs self-s...
research
∙
02/16/2021
SCAPE: Learning Stiffness Control from Augmented Position Control Experiences
We introduce a sample-efficient method for learning state-dependent stif...
research
∙
12/02/2020
Value Alignment Verification
As humans interact with autonomous agents to perform increasingly compli...
research
∙
09/28/2020
The EMPATHIC Framework for Task Learning from Implicit Human Feedback
Reactions such as gestures, facial expressions, and vocalizations are an...
research
∙
08/24/2020
ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory
Robots in human environments will need to interact with a wide variety o...
research
∙
07/30/2020
PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards
Reinforcement learning (RL), particularly in sparse reward settings, oft...
research
∙
07/24/2020
Bayesian Robust Optimization for Imitation Learning
One of the main challenges in imitation learning is determining what act...
research
∙
02/28/2020
Efficiently Guiding Imitation Learning Algorithms with Human Gaze
Human gaze is known to be an intention-revealing signal in human demonst...
research
∙
02/21/2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
Bayesian reward learning from demonstrations enables rigorous safety and...
research
∙
02/09/2020
Local Nonparametric Meta-Learning
A central goal of meta-learning is to find a learning rule that enables ...
research
∙
12/10/2019
Deep Bayesian Reward Learning from Preferences
Bayesian inverse reinforcement learning (IRL) methods are ideal for safe...
research
∙
07/21/2019
Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty
Sudden changes in the dynamics of robotic tasks, such as contact with an...
research
∙
07/16/2019
Understanding Teacher Gaze Patterns for Robot Learning
Human gaze is known to be a strong indicator of underlying human intenti...
research
∙
07/09/2019
Ranking-Based Reward Extrapolation without Rankings
The performance of imitation learning is typically upper-bounded by the ...
research
∙
07/06/2019
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
A key challenge in intelligent robotics is creating robots that are capa...
research
∙
05/27/2019
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning
Deep reinforcement learning encompasses many versatile tools for designi...
research
∙
05/07/2019
Uncertainty-Aware Data Aggregation for Deep Imitation Learning
Estimating statistical uncertainties allows autonomous agents to communi...
research
∙
04/12/2019
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
A critical flaw of existing inverse reinforcement learning (IRL) methods...
research
∙
03/05/2019
Using Natural Language for Reward Shaping in Reinforcement Learning
Recent reinforcement learning (RL) approaches have shown strong performa...
research
∙
01/08/2019
Risk-Aware Active Inverse Reinforcement Learning
Active learning from demonstration allows a robot to query a human for s...
research
∙
11/08/2018
LAAIR: A Layered Architecture for Autonomous Interactive Robots
When developing general purpose robots, the overarching software archite...
research
∙
10/02/2018
Towards Online Learning from Corrective Demonstrations
Robots operating in real-world human environments will likely encounter ...
research
∙
06/29/2018
Learning Multi-Step Robotic Tasks from Observation
Due to burdensome data requirements, learning from demonstration often f...
research
∙
06/04/2018
Importance Sampling Policy Evaluation with an Estimated Behavior Policy
In reinforcement learning, off-policy evaluation is the task of using da...
research
∙
05/20/2018
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications
Inverse reinforcement learning (IRL) infers a reward function from demon...
research
∙
02/12/2018
Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics
Noisy observations coupled with nonlinear dynamics pose one of the bigge...
research
∙
02/12/2018
Leveraging Task Knowledge for Robot Motion Planning Under Uncertainty
Noisy observations coupled with nonlinear dynamics pose one of the bigge...
research
∙
08/29/2017
Safe Reinforcement Learning via Shielding
Reinforcement learning algorithms discover policies that maximize reward...
research
∙
07/03/2017
Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning
In the field of reinforcement learning there has been recent progress to...
research
∙
06/12/2017
Data-Efficient Policy Evaluation Through Behavior Policy Search
We consider the task of evaluating a policy for a Markov decision proces...
research
∙
06/20/2016