227 citations · 241 across the 4 of their papers we have counts for
5 papers
BATS: Best Action Trajectory Stitching
Ian Char, Viraj Mehta, Adam Villaflor +2
The problem of offline reinforcement learning focuses on learning a good policy from a log of environment interactions. Past efforts for developing algorithms in this area have rev…
Learning to Robustly Negotiate Bi-Directional Lane Usage in High-Conflict Driving Scenarios
Christoph Killing, Adam Villaflor, John M. Dolan
Recently, autonomous driving has made substantial progress in addressing the most common traffic scenarios like intersection navigation and lane changing. However, most of these su…
Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation
Gregory Kahn, Adam Villaflor, Pieter Abbeel +1
A general-purpose intelligent robot must be able to learn autonomously and be able to accomplish multiple tasks in order to be deployed in the real world. However, standard reinfor…
Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation
Gregory Kahn, Adam Villaflor, Bosen Ding +2
Enabling robots to autonomously navigate complex environments is essential for real-world deployment. Prior methods approach this problem by having the robot maintain an internal m…
Uncertainty-Aware Reinforcement Learning for Collision Avoidance
Gregory Kahn, Adam Villaflor, Vitchyr Pong +2
Reinforcement learning can enable complex, adaptive behavior to be learned automatically for autonomous robotic platforms. However, practical deployment of reinforcement learning m…