research
∙
11/04/2022
The Benefits of Model-Based Generalization in Reinforcement Learning
Model-Based Reinforcement Learning (RL) is widely believed to have the p...
share
research
∙
07/04/2022
Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions
Value iteration (VI) is a foundational dynamic programming method, impor...
research
∙
10/14/2021
Hindsight Network Credit Assignment: Efficient Credit Assignment in Networks of Discrete Stochastic Units
Training neural networks with discrete stochastic variables presents a u...
research
∙
11/24/2020
Hindsight Network Credit Assignment
We present Hindsight Network Credit Assignment (HNCA), a novel learning ...
research
∙
10/28/2020
Understanding the Pathologies of Approximate Policy Evaluation when Combined with Greedification in Reinforcement Learning
Despite empirical success, the theory of reinforcement learning (RL) wit...
research
∙
11/19/2019
Variance Reduced Advantage Estimation with δ Hindsight Credit Assignment
Hindsight Credit Assignment (HCA) refers to a recently proposed family o...
research
∙
03/07/2019
MinAtar: An Atari-inspired Testbed for More Efficient Reinforcement Learning Experiments
The Arcade Learning Environment (ALE) is a popular platform for evaluati...
research
∙
05/10/2018
Metatrace: Online Step-size Tuning by Meta-gradient Descent for Reinforcement Learning Control
Reinforcement learning (RL) has had many successes in both "deep" and "s...
research
∙
01/25/2018
Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods
This paper investigates estimating the variance of a temporal-difference...
research
∙
04/26/2017
