16 citations · 47 across the 21 of their papers we have counts for
4 papers · 1 filter
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning
Michelle A. Lee, Carlos Florensa, Jonathan Tremblay +4
Traditional robotic approaches rely on an accurate model of the environment, a detailed description of how to perform the task, and a robust perception system to keep track of the…
Inferring the Material Properties of Granular Media for Robotic Tasks
Carolyn Matl, Yashraj Narang, Ruzena Bajcsy +2
Granular media (e.g., cereal grains, plastic resin pellets, and pills) are ubiquitous in robotics-integrated industries, such as agriculture, manufacturing, and pharmaceutical deve…
DISCO: Double Likelihood-free Inference Stochastic Control
Lucas Barcelos, Rafael Oliveira, Rafael Possas +2
Accurate simulation of complex physical systems enables the development, testing, and certification of control strategies before they are deployed into the real systems. As simulat…
Reinforcement Learning with Probabilistically Complete Exploration
Philippe Morere, Gilad Francis, Tom Blau +1
Balancing exploration and exploitation remains a key challenge in reinforcement learning (RL). State-of-the-art RL algorithms suffer from high sample complexity, particularly in th…