Randomized Value Functions via Posterior State-Abstraction Sampling

5 October 2020

Papers citing "Randomized Value Functions via Posterior State-Abstraction Sampling"

6 / 6 papers shown

Title
Sharing Knowledge in Multi-Task Deep Reinforcement Learning Carlo DÉramo Davide Tateo Andrea Bonarini Marcello Restelli Jan Peters 48 122 0 17 Jan 2024
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy 19 4 0 30 Oct 2022
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification James A. Grant David S. Leslie 34 3 0 29 Sep 2021
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control Amrit Singh Bedi Anjaly Parayil Junyu Zhang Mengdi Wang Alec Koppel 22 15 0 15 Jun 2021
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 104 194 0 07 Feb 2020
Building machines that adapt and compute like brains Brenden Lake J. Tenenbaum AI4CE FedML NAI AILaw 243 890 0 11 Nov 2017