Incorporating Explicit Uncertainty Estimates into Deep Offline
Reinforcement Learning

Incorporating Explicit Uncertainty Estimates into Deep Offline Reinforcement Learning

2 June 2022

David Brandfonbrener

Rémi Tachet des Combes

Papers citing "Incorporating Explicit Uncertainty Estimates into Deep Offline Reinforcement Learning"

9 / 9 papers shown

Title
Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses Thanh Nguyen T. Luu Tri Ton Chang D. Yoo OffRL AAML 34 0 0 18 May 2024
Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning Hongyu Zang Xin-hui Li Leiji Zhang Yang Liu Baigui Sun Riashat Islam Rémi Tachet des Combes Romain Laroche OffRL 29 5 0 26 Oct 2023
More for Less: Safe Policy Improvement With Stronger Performance Guarantees Patrick Wienhoft Marnix Suilen T. D. Simão Clemens Dubslaff C. Baier N. Jansen OffRL 16 6 0 13 May 2023
Safe Policy Improvement for POMDPs via Finite-State Controllers T. D. Simão Marnix Suilen N. Jansen OffRL 24 9 0 12 Jan 2023
Offline Reinforcement Learning with Implicit Q-Learning Ilya Kostrikov Ashvin Nair Sergey Levine OffRL 214 839 0 12 Oct 2021
COMBO: Conservative Offline Model-Based Policy Optimization Tianhe Yu Aviral Kumar Rafael Rafailov Aravind Rajeswaran Sergey Levine Chelsea Finn OffRL 219 413 0 16 Feb 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 340 1,955 0 04 May 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015