Implicit Quantile Networks for Distributional Reinforcement Learning

14 June 2018

David Silver

Papers citing "Implicit Quantile Networks for Distributional Reinforcement Learning"

50 / 112 papers shown

Title
Flow Models for Unbounded and Geometry-Aware Distributional Reinforcement Learning Simo Alami C. Rim Kaddah Jesse Read Marie-Paule Cani 53 0 0 07 May 2025
Return Capping: Sample-Efficient CVaR Policy Gradient Optimisation Harry Mead Clarissa Costen Bruno Lacerda Nick Hawes 26 0 0 29 Apr 2025
IGN : Implicit Generative Networks Haozheng Luo Tianyi Wu Feiyu Han Zhijun Yan OffRL 37 1 0 24 Feb 2025
On Generalization and Distributional Update for Mimicking Observations with Adequate Exploration Yirui Zhou Xiaowei Liu Xiaofeng Zhang Yangchun Zhang 41 0 0 22 Jan 2025
Risk-averse policies for natural gas futures trading using distributional reinforcement learning Félicien Hêche Biagio Nigro Oussama Barakat Stephan Robert-Nicoud OffRL 46 0 0 08 Jan 2025
Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning Mehrdad Moghimi Hyejin Ku OffRL 48 0 0 03 Jan 2025
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC Tyler Clark Mark Towers Christine Evers Jonathon Hare OffRL 40 0 0 06 Nov 2024
Deep Generative Quantile Bayes Jungeum Kim Percy S. Zhai Veronika Rockova 53 0 0 10 Oct 2024
The Central Role of the Loss Function in Reinforcement Learning Kaiwen Wang Nathan Kallus Wen Sun OffRL 64 7 0 19 Sep 2024
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation Taehyun Cho Seung Han Kyungjae Lee Seokhun Ju Dohyeong Kim Jungwoo Lee 72 0 0 31 Jul 2024
Bigger, Regularized, Optimistic: scaling for compute and sample-efficient continuous control Michal Nauman M. Ostaszewski Krzysztof Jankowski Piotr Milo's Marek Cygan OffRL 52 17 0 25 May 2024
Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence Minheng Xiao Xian Yu Lei Ying 44 2 0 23 May 2024
CTD4 -- A Deep Continuous Distributional Actor-Critic Agent with a Kalman Fusion of Multiple Critics David Valencia Henry Williams Trevor Gee Bruce A MacDonaland Minas V. Liarokapis Minas Liarokapis OffRL 40 2 0 04 May 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 44 3 0 28 Feb 2024
Collaborative Reinforcement Learning Based Unmanned Aerial Vehicle (UAV) Trajectory Design for 3D UAV Tracking Yujiao Zhu Ming Chen Sihua Wang Ye Hu Yuchen Liu Changchuan Yin 26 5 0 22 Jan 2024
UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systems Changshuo Zhang Sirui Chen Xiao Zhang Sunhao Dai Weijie Yu Jun Xu OffRL 45 1 0 17 Jan 2024
Multi-agent Reinforcement Learning: A Comprehensive Survey Dom Huh Prasant Mohapatra AI4CE 36 8 0 15 Dec 2023
An Invitation to Deep Reinforcement Learning Bernhard Jaeger Andreas Geiger OffRL OOD 80 5 0 13 Dec 2023
Learning to Simulate: Generative Metamodeling via Quantile Regression L. Hong Yanxi Hou Qingkai Zhang Xiaowei Zhang 30 1 0 29 Nov 2023
On the Theory of Risk-Aware Agents: Bridging Actor-Critic and Economics Michal Nauman Marek Cygan 40 1 0 30 Oct 2023
Novelty Detection in Reinforcement Learning with World Models Geigh Zollicoffer Kenneth Eaton Jonathan C. Balloch Julia Kim Mark O. Riedl Robert Wright Mark O. Riedl 30 1 0 12 Oct 2023
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 46 4 0 05 Oct 2023
Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning Lukas Schneider Jonas Frey Takahiro Miki Marco Hutter 37 9 0 25 Sep 2023
Bag of Policies for Distributional Deep Exploration Asen Nachkov Luchen Li Giulia Luise Filippo Valdettaro Aldo A. Faisal OffRL 43 0 0 03 Aug 2023
Is Risk-Sensitive Reinforcement Learning Properly Resolved? Ruiwen Zhou Minghuan Liu Kan Ren Xufang Luo Weinan Zhang Dongsheng Li 27 2 0 02 Jul 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz A. Zanger Wendelin Bohmer M. Spaan 38 4 0 12 Jun 2023
Policy-Based Self-Competition for Planning Problems Jonathan Pirnay Q. Göttl Jakob Burger D. G. Grimm 49 3 0 07 Jun 2023
Bigger, Better, Faster: Human-level Atari with human-level efficiency Max Schwarzer J. Obando-Ceron Rameswar Panda Marc G. Bellemare Rishabh Agarwal Pablo Samuel Castro OffRL 54 85 0 30 May 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 30 20 0 29 May 2023
On the Value of Myopic Behavior in Policy Reuse Kang Xu Chenjia Bai Shuang Qiu Haoran He Bin Zhao Zhen Wang Wei Li Xuelong Li 41 1 0 28 May 2023
Latent-Conditioned Policy Gradient for Multi-Objective Deep Reinforcement Learning T. Kanazawa Chetan Gupta 31 0 0 15 Mar 2023
Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning Ji-Yun Oh Joonkee Kim Minchan Jeong Se-Young Yun 38 1 0 03 Mar 2023
Distributional Method for Risk Averse Reinforcement Learning Ziteng Cheng S. Jaimungal Nick G. Martin 24 0 0 27 Feb 2023
Distributional GFlowNets with Quantile Flows Dinghuai Zhang L. Pan Ricky T. Q. Chen Aaron Courville Yoshua Bengio 34 25 0 11 Feb 2023
Distillation Policy Optimization Jianfei Ma OffRL 26 1 0 01 Feb 2023
Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning James Queeney M. Benosman OOD OffRL 43 5 0 30 Jan 2023
Train Hard, Fight Easy: Robust Meta Reinforcement Learning Ido Greenberg Shie Mannor Gal Chechik E. Meirom OffRL OOD 23 6 0 26 Jan 2023
Predictive World Models from Real-World Partial Observations Robin Karlsson Alexander Carballo Keisuke Fujii Kento Ohtani K. Takeda 49 5 0 12 Jan 2023
Risk-Sensitive Policy with Distributional Reinforcement Learning Thibaut Théate D. Ernst OffRL 32 5 0 30 Dec 2022
Confidence-Conditioned Value Functions for Offline Reinforcement Learning Joey Hong Aviral Kumar Sergey Levine OffRL 39 20 0 08 Dec 2022
Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability Whiyoung Jung Myungsik Cho Jongeui Park Young-Jin Sung 38 4 0 28 Nov 2022
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds Hao Liang Zhihui Luo 30 14 0 25 Oct 2022
Solving Continuous Control via Q-learning Tim Seyde Peter Werner Wilko Schwarting Igor Gilitschenski Martin Riedmiller Daniela Rus Markus Wulfmeier OffRL LRM 39 22 0 22 Oct 2022
Probing Transfer in Deep Reinforcement Learning without Task Engineering Andrei A. Rusu Sebastian Flennerhag Dushyant Rao Razvan Pascanu R. Hadsell 39 6 0 22 Oct 2022
Regret Bounds for Risk-Sensitive Reinforcement Learning Osbert Bastani Y. Ma E. Shen Wei Xu 46 18 0 11 Oct 2022
MAN: Multi-Action Networks Learning Keqin Wang Alison Bartsch A. Farimani 21 3 0 19 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 37 4 0 17 Sep 2022
Prediction Based Decision Making for Autonomous Highway Driving Mustafa Yildirim Sajjad Mozaffari Lucy McCutcheon M. Dianati Alireza Tamaddoni-Nezhad Saber Fallah 16 7 0 05 Sep 2022
A Risk-Sensitive Approach to Policy Optimization Jared Markowitz Ryan W. Gardner Ashley J. Llorens R. Arora I-J. Wang OffRL 36 6 0 19 Aug 2022
A Maintenance Planning Framework using Online and Offline Deep Reinforcement Learning Zaharah Bukhsh N. Jansen Hajo Molegraaf OffRL AI4CE 32 6 0 01 Aug 2022