Estimating Risk and Uncertainty in Deep Reinforcement Learning

23 May 2019

W. Clements

B. V. Delft

Benoît-Marie Robaglia

Reda Bahi Slaoui

Sébastien Toth

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Papers citing "Estimating Risk and Uncertainty in Deep Reinforcement Learning"

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Title
Disentangling Uncertainty for Safe Social Navigation using Deep Reinforcement Learning Daniel Flögel Marcos Gómez Villafane Joshua Ransiek Sören Hohmann 28 0 0 16 Sep 2024
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning Parvin Malekzadeh Ming Hou Konstantinos N. Plataniotis 51 1 0 16 Oct 2023
Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty Carlos Quintero-Peña Wil Thomason Bo Xiong Anastasios Kyrillidis Lydia E. Kavraki 18 7 0 28 Sep 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz A. Zanger Wendelin Bohmer M. Spaan 30 4 0 12 Jun 2023
Distributional constrained reinforcement learning for supply chain optimization J. Berm\údez Antonio del Rio-Chanona Calvin Tsay 26 5 0 03 Feb 2023
Anti-Exploration by Random Network Distillation Alexander Nikulin Vladislav Kurenkov Denis Tarasov Sergey Kolesnikov 38 24 0 31 Jan 2023
Generating and Detecting True Ambiguity: A Forgotten Danger in DNN Supervision Testing Michael Weiss A. Gómez Paolo Tonella AAML 18 6 0 21 Jul 2022
Safer Autonomous Driving in a Stochastic, Partially-Observable Environment by Hierarchical Contingency Planning Ugo Lecerf Christelle Yemdji Tchassi Pietro Michiardi 30 1 0 13 Apr 2022
Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios Ugo Lecerf Christelle Yemdji Tchassi S. Aubert Pietro Michiardi 24 0 0 11 Apr 2022
Adaptive Risk-Tendency: Nano Drone Navigation in Cluttered Environments with Distributional Reinforcement Learning Cheng Liu E. Kampen Guido de Croon 34 16 0 28 Mar 2022
Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation Vincent Mai Kaustubh Mani Liam Paull 36 34 0 05 Jan 2022
Learning to Be Cautious Montaser Mohammedalamen Dustin Morrill Alexander Sieusahai Yash Satsangi Michael Bowling 18 3 0 29 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 41 81 0 26 Oct 2021
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction Moitreya Chatterjee Narendra Ahuja A. Cherian UQCV VGen BDL 42 17 0 06 Oct 2021
A study of first-passage time minimization via Q-learning in heated gridworlds M. A. Larchenko Pavel Osinenko Grigory Yaremenko V. V. Palyulin 26 4 0 05 Oct 2021
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble Gaon An Seungyong Moon Jang-Hyun Kim Hyun Oh Song OffRL 105 262 0 04 Oct 2021
Enabling risk-aware Reinforcement Learning for medical interventions through uncertainty decomposition Paul Festor Giulia Luise Matthieu Komorowski A. Faisal UD OffRL 22 10 0 16 Sep 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 36 93 0 14 Sep 2021
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning Yue Wu Shuangfei Zhai Nitish Srivastava J. Susskind Jian Zhang Ruslan Salakhutdinov Hanlin Goh EDL OffRL OnRL 21 184 0 17 May 2021
Safe Chance Constrained Reinforcement Learning for Batch Process Control M. Mowbray Panagiotis Petsagkourakis Ehecatl Antonio del Rio Chanona Dongda Zhang OffRL 34 34 0 23 Apr 2021
Risk-Averse Bayes-Adaptive Reinforcement Learning Marc Rigter Bruno Lacerda Nick Hawes 27 41 0 10 Feb 2021
Should artificial agents ask for help in human-robot collaborative problem-solving? Adrien Bennetot V. Charisi Natalia Díaz Rodríguez 21 8 0 25 May 2020
Application of Deep Q-Network in Portfolio Management Ziming Gao Yuan Gao Yitao Hu Zhengyong Jiang Jionglong Su AIFin 16 49 0 13 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015