9 citations · 16 across the 3 of their papers we have counts for
3 papers
A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation
TRI LBM Team, Jose Barreiros, Andrew Beaulieu +79
Robot manipulation has seen tremendous progress in recent years, with imitation learning policies enabling successful performance of dexterous and hard-to-model tasks. Concurrently…
Driving in Real Life with Inverse Reinforcement Learning
Tung Phan-Minh, Forbes Howington, Ting-Sheng Chu +10
In this paper, we introduce the first learning-based planner to drive a car in dense, urban traffic using Inverse Reinforcement Learning (IRL). Our planner, DriveIRL, generates a d…
Efficient Ridesharing Dispatch Using Multi-Agent Reinforcement Learning
Oscar de Lima, Hansal Shah, Ting-Sheng Chu +1
With the advent of ride-sharing services, there is a huge increase in the number of people who rely on them for various needs. Most of the earlier approaches tackling this issue re…