research
∙
04/03/2023
Empirical Design in Reinforcement Learning
Empirical design in reinforcement learning is no small task. Running goo...
share
research
∙
05/17/2022
Robust Losses for Learning Value Functions
Most value function learning algorithms in reinforcement learning are ba...
research
∙
02/04/2022
A Temporal-Difference Approach to Policy Gradient Estimation
The policy gradient theorem (Sutton et al., 2000) prescribes the usage o...
research
∙
04/28/2021
A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning
Many reinforcement learning algorithms rely on value estimation. However...
research
∙
09/08/2020
ℛℒ_1-𝒢𝒫: Safe Simultaneous Learning and Control
We present ℛℒ_1-𝒢𝒫, a control framework that enables safe simultaneous l...
research
∙
07/01/2020
Gradient Temporal-Difference Learning with Regularized Corrections
It is still common to use Q-learning and temporal difference (TD) learni...
research
∙
02/05/2020
Learning Probabilistic Intersection Traffic Models for Trajectory Prediction
Autonomous agents must be able to safely interact with other vehicles to...
research
∙
04/04/2019
Intent-Aware Probabilistic Trajectory Estimation for Collision Prediction with Uncertainty Quantification
Collision prediction in a dynamic and unknown environment relies on know...
research
∙
02/13/2019
Proximity Queries for Absolutely Continuous Parametric Curves
In motion planning problems for autonomous robots, such as self-driving ...
research
∙
11/06/2018
Online Off-policy Prediction
This paper investigates the problem of online prediction learning, where...
research
∙
07/18/2018
General Value Function Networks
In this paper we show that restricting the representation-layer of a Rec...
research
∙
06/12/2018