Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation

5 January 2022

Papers citing "Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation"

23 / 23 papers shown

Title
Guaranteeing Out-Of-Distribution Detection in Deep RL via Transition Estimation Mohit Prashant Arvind Easwaran Suman Das Michael Yuhas OffRL 69 1 0 07 Mar 2025
SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning Xu Wan Chao Yang Cheng Yang Jie Song Mingyang Sun 63 0 0 03 Mar 2025
Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning Seyeon Kim Joonhun Lee Namhoon Cho Sungjun Han Seungeon Baek 39 0 0 05 Aug 2024
Detecting Unsafe Behavior in Neural Network Imitation Policies for Caregiving Robotics Andrii Tytarenko OffRL 44 0 0 29 Jul 2024
Contextualized Hybrid Ensemble Q-learning: Learning Fast with Control Priors Emma Cramer Bernd Frauenknecht Ramil Sabirov Sebastian Trimpe OffRL OnRL 46 3 0 28 Jun 2024
Uncertainty-Aware Reward-Free Exploration with General Function Approximation Junkai Zhang Weitong Zhang Dongruo Zhou Q. Gu 54 3 0 24 Jun 2024
Learning to Play Atari in a World of Tokens Pranav Agarwal Sheldon Andrews Samira Ebrahimi Kahou OffRL 30 0 0 03 Jun 2024
Grid-Mapping Pseudo-Count Constraint for Offline Reinforcement Learning Yi Shen Hanyan Huang Shan Xie 37 0 0 03 Apr 2024
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty Parvin Malekzadeh Ming Hou Konstantinos N. Plataniotis UD 23 2 0 05 Jan 2024
Uncertainty-Aware Decision Transformer for Stochastic Driving Environments Zenan Li Fan Nie Q. Sun Fang Da Hang Zhao OffRL 23 3 0 28 Sep 2023
An Architecture for Deploying Reinforcement Learning in Industrial Environments Georg Schafer Reuf Kozlica S. Wegenkittl Stefan Huber OffRL AI4CE 20 5 0 02 Jun 2023
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs Junkai Zhang Weitong Zhang Quanquan Gu 33 3 0 17 Mar 2023
MEET: A Monte Carlo Exploration-Exploitation Trade-off for Buffer Sampling Julius Ott Lorenzo Servadei Jose A. Arjona-Medina E. Rinaldi Gianfranco Mauro Daniela Sanchez Lopera Michael Stephan Thomas Stadelmayer Avik Santra Robert Wille 23 0 0 24 Oct 2022
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient Ming Yin Mengdi Wang Yu-Xiang Wang OffRL 74 12 0 03 Oct 2022
Normality-Guided Distributional Reinforcement Learning for Continuous Control Ju-Seung Byun Andrew Perrault OffRL 16 0 0 28 Aug 2022
Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration Zijian Gao Yiying Li Kele Xu Yuanzhao Zhai Dawei Feng Bo Ding Xinjun Mao Huaimin Wang 32 0 0 24 Aug 2022
A Review of Uncertainty for Deep Reinforcement Learning Owen Lockwood Mei Si 11 38 0 18 Aug 2022
Nuclear Norm Maximization Based Curiosity-Driven Learning Chao Chen Zijian Gao Kele Xu Sen Yang Yiying Li Bo Ding Dawei Feng Huaimin Wang 137 5 0 21 May 2022
DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning Hassam Sheikh Kizza M Nandyose Frisbee Mariano Phielipp 17 8 0 31 Jan 2022
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 202 81 0 16 Feb 2021
Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review Rongrong Liu F. Nageotte P. Zanne M. de Mathelin Birgitta Dresp 42 143 0 08 Feb 2021
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