Fully Parameterized Quantile Function for Distributional Reinforcement Learning

5 November 2019

Jiang Bian

Papers citing "Fully Parameterized Quantile Function for Distributional Reinforcement Learning"

22 / 22 papers shown

Title
Flow Models for Unbounded and Geometry-Aware Distributional Reinforcement Learning Simo Alami C. Rim Kaddah Jesse Read Marie-Paule Cani 51 0 0 07 May 2025
IGN : Implicit Generative Networks Haozheng Luo Tianyi Wu Feiyu Han Zhijun Yan OffRL 29 1 0 24 Feb 2025
On Generalization and Distributional Update for Mimicking Observations with Adequate Exploration Yirui Zhou Xiaowei Liu Xiaofeng Zhang Yangchun Zhang 37 0 0 22 Jan 2025
Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning Mehrdad Moghimi Hyejin Ku OffRL 43 0 0 03 Jan 2025
Foundations of Multivariate Distributional Reinforcement Learning Harley Wiltzer Jesse Farebrother Arthur Gretton Mark Rowland OffRL 43 2 0 31 Aug 2024
Multi-agent Reinforcement Learning: A Comprehensive Survey Dom Huh Prasant Mohapatra AI4CE 36 8 0 15 Dec 2023
Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning Lukas Schneider Jonas Frey Takahiro Miki Marco Hutter 30 9 0 25 Sep 2023
Cramer Type Distances for Learning Gaussian Mixture Models by Gradient Descent Ruichong Zhang 28 0 0 13 Jul 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz A. Zanger Wendelin Bohmer M. Spaan 25 4 0 12 Jun 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 19 0 0 27 Feb 2023
Distributional GFlowNets with Quantile Flows Dinghuai Zhang L. Pan Ricky T. Q. Chen Aaron Courville Yoshua Bengio 29 25 0 11 Feb 2023
Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability Whiyoung Jung Myungsik Cho Jongeui Park Young-Jin Sung 35 4 0 28 Nov 2022
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds Hao Liang Zhihui Luo 23 14 0 25 Oct 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 30 4 0 17 Sep 2022
Reinforcement Learning with Heterogeneous Data: Estimation and Inference Elynn Y. Chen Rui Song Michael I. Jordan OffRL 21 10 0 31 Jan 2022
Reinforcement Learning for Personalized Drug Discovery and Design for Complex Diseases: A Systems Pharmacology Perspective Ryan K. Tan Yang Liu Lei Xie 37 2 0 21 Jan 2022
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning Yingjie Fei Zhuoran Yang Yudong Chen Zhaoran Wang 41 46 0 06 Nov 2021
Evolutionary Self-Replication as a Mechanism for Producing Artificial Intelligence Samuel Schmidgall Joe Hays 41 1 0 16 Sep 2021
Enabling risk-aware Reinforcement Learning for medical interventions through uncertainty decomposition Paul Festor Giulia Luise Matthieu Komorowski A. Faisal UD OffRL 20 10 0 16 Sep 2021
Conservative Offline Distributional Reinforcement Learning Yecheng Jason Ma Dinesh Jayaraman Osbert Bastani OffRL 70 78 0 12 Jul 2021
QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning Jian Hu Seth Austin Harding Haibin Wu Siyue Hu Shih-Wei Liao 29 9 0 09 Sep 2020