research
∙
09/19/2023
Explaining Agent Behavior with Large Language Models
Intelligent agents such as robots are increasingly deployed in real-worl...
share
research
∙
07/03/2023
Theory of Mind as Intrinsic Motivation for Multi-Agent Reinforcement Learning
The ability to model the mental states of others is crucial to human soc...
research
∙
06/21/2023
Introspective Action Advising for Interpretable Transfer Learning
Transfer learning can be applied in deep reinforcement learning to accel...
research
∙
05/25/2023
Characterizing Out-of-Distribution Error via Optimal Transport
Out-of-distribution (OOD) data poses serious challenges in deployed mach...
research
∙
02/23/2023
Concept Learning for Interpretable Multi-Agent Reinforcement Learning
Multi-agent robotic systems are increasingly operating in real-world env...
research
∙
11/15/2022
Explainable Action Advising for Multi-Agent Reinforcement Learning
Action advising is a knowledge transfer technique for reinforcement lear...
research
∙
08/01/2022
A System for Imitation Learning of Contact-Rich Bimanual Manipulation Policies
In this paper, we discuss a framework for teaching bimanual manipulation...
research
∙
10/22/2020
Language-Conditioned Imitation Learning for Robot Manipulation Tasks
Imitation learning is a popular approach for teaching motor skills to ro...
research
∙
11/26/2019
Imitation Learning of Robot Policies by Combining Language, Vision and Demonstration
In this work we propose a novel end-to-end imitation learning approach w...
research
∙
11/15/2019
Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient
Model-free reinforcement learning algorithms such as Deep Deterministic ...
research
∙
08/15/2019
Learning Interactive Behaviors for Musculoskeletal Robots Using Bayesian Interaction Primitives
Musculoskeletal robots that are based on pneumatic actuation have a vari...
research
∙
08/14/2019
