Distributional Reinforcement Learning with Quantile Regression

27 October 2017

Papers citing "Distributional Reinforcement Learning with Quantile Regression"

50 / 401 papers shown

Title
Deep Learning Tubes for Tube MPC David D. Fan Ali-akbar Agha-mohammadi Evangelos A. Theodorou 32 57 0 05 Feb 2020
Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors Jingliang Duan Yang Guan Shengbo Eben Li Yangang Ren B. Cheng OffRL 25 174 0 09 Jan 2020
Sample-based Distributional Policy Gradient Rahul Singh Keuntaek Lee Yongxin Chen 23 19 0 08 Jan 2020
A Survey of Deep Reinforcement Learning in Video Games Kun Shao Zhentao Tang Yuanheng Zhu Nannan Li Dongbin Zhao OffRL AI4TS 43 188 0 23 Dec 2019
Adapting Behaviour for Learning Progress Tom Schaul Diana Borsa David Ding David Szepesvari Georg Ostrovski Will Dabney Simon Osindero 22 18 0 14 Dec 2019
Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion Bo Zhou Hongsheng Zeng Fan Wang Yunxiang Li Hao Tian 11 18 0 10 Dec 2019
Worst Cases Policy Gradients Yichuan Tang Jian Zhang Ruslan Salakhutdinov 27 75 0 09 Nov 2019
Distributional Reward Decomposition for Reinforcement Learning Zichuan Lin Li Zhao Derek Yang Tao Qin Guangwen Yang Tie-Yan Liu OffRL 13 15 0 06 Nov 2019
Fully Parameterized Quantile Function for Distributional Reinforcement Learning Derek Yang Li Zhao Zichuan Lin Tao Qin Jiang Bian Tie-Yan Liu OOD OffRL 26 135 0 05 Nov 2019
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy Ramtin Keramati Christoph Dann Alex Tamkin Emma Brunskill 19 75 0 05 Nov 2019
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians Axel Brando Jose A. Rodríguez-Serrano Jordi Vitrià Alberto Rubio 6 21 0 27 Oct 2019
Benchmarking Batch Deep Reinforcement Learning Algorithms Shih-Han Chou Wen-Yen Chang W. Hsu Jianlong Fu OffRL 27 182 0 03 Oct 2019
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping Cristian Bodnar A. Li Karol Hausman P. Pastor Mrinal Kalakrishnan OffRL 28 50 0 01 Oct 2019
An Open-Source Framework for Adaptive Traffic Signal Control Wade Genders S. Razavi 19 29 0 01 Sep 2019
An Optimistic Perspective on Offline Reinforcement Learning Rishabh Agarwal Dale Schuurmans Mohammad Norouzi OffRL OnRL 36 69 0 10 Jul 2019
General non-linear Bellman equations H. V. Hasselt John Quan Matteo Hessel Zhongwen Xu Diana Borsa André Barreto 29 14 0 08 Jul 2019
Learning Policies through Quantile Regression Oliver Richter Roger Wattenhofer 16 0 0 27 Jun 2019
Modern Deep Reinforcement Learning Algorithms Sergey Ivanov A. Dýakonov OffRL 29 39 0 24 Jun 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning Carles Gelada Saurabh Kumar Jacob Buckman Ofir Nachum Marc G. Bellemare BDL 24 281 0 06 Jun 2019
Distributional Policy Optimization: An Alternative Approach for Continuous Control Chen Tessler Guy Tennenholtz Shie Mannor OffRL 18 44 0 23 May 2019
Estimating Risk and Uncertainty in Deep Reinforcement Learning W. Clements B. V. Delft Benoît-Marie Robaglia Reda Bahi Slaoui Sébastien Toth 30 96 0 23 May 2019
COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration Nicholas Watters Loic Matthey Matko Bosnjak Christopher P. Burgess Alexander Lerchner OffRL 19 117 0 22 May 2019
Stochastically Dominant Distributional Reinforcement Learning John D. Martin Michal Lyskawinski Xiaohu Li Brendan Englot 23 24 0 17 May 2019
Distributional Reinforcement Learning for Efficient Exploration B. Mavrin Shangtong Zhang Hengshuai Yao Linglong Kong Kaiwen Wu Yaoliang Yu OOD OffRL 22 87 0 13 May 2019
Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning, Extended version Erwan Lecarpentier Emmanuel Rachelson 21 82 0 22 Apr 2019
Deep Reinforcement Learning with Decorrelation B. Mavrin Hengshuai Yao Linglong Kong 37 8 0 18 Mar 2019
Machine Learning in IoT Security: Current Solutions and Future Challenges Fatima Hussain Rasheed Hussain Syed Ali Hassan Ekram Hossain 37 519 0 14 Mar 2019
Catalyst.RL: A Distributed Framework for Reproducible RL Research Sergey Kolesnikov Oleksii Hrinchuk OffRL 25 8 0 28 Feb 2019
Statistics and Samples in Distributional Reinforcement Learning Mark Rowland Robert Dadashi Saurabh Kumar Rémi Munos Marc G. Bellemare Will Dabney OffRL 14 88 0 21 Feb 2019
Distributional reinforcement learning with linear function approximation Marc G. Bellemare Nicolas Le Roux Pablo Samuel Castro Subhodeep Moitra 74 23 0 08 Feb 2019
Artificial Intelligence for Prosthetics - challenge solutions L. Kidzinski Carmichael F. Ong Sharada Mohanty Jennifer Hicks Sean F. Carroll ... E. Tumer J. Watson M. Salathé Sergey Levine Scott L. Delp 15 40 0 07 Feb 2019
A Comparative Analysis of Expected and Distributional Reinforcement Learning Clare Lyle Pablo Samuel Castro Marc G. Bellemare OffRL 9 78 0 30 Jan 2019
A Theoretical Analysis of Deep Q-Learning Jianqing Fan Zhuoran Yang Yuchen Xie Zhaoran Wang 28 596 0 01 Jan 2019
Information-Directed Exploration for Deep Reinforcement Learning Nikolay Nikolov Johannes Kirschner Felix Berkenkamp Andreas Krause 31 68 0 18 Dec 2018
Dopamine: A Research Framework for Deep Reinforcement Learning Pablo Samuel Castro Subhodeep Moitra Carles Gelada Saurabh Kumar Marc G. Bellemare OffRL 28 276 0 14 Dec 2018
An Introduction to Deep Reinforcement Learning Vincent François-Lavet Peter Henderson Riashat Islam Marc G. Bellemare Joelle Pineau OffRL AI4CE 88 1,236 0 30 Nov 2018
Reward learning from human preferences and demonstrations in Atari Borja Ibarz Jan Leike Tobias Pohlen G. Irving Shane Legg Dario Amodei 33 387 0 15 Nov 2018
QUOTA: The Quantile Option Architecture for Reinforcement Learning Fengxiang Yang Zhun Zhong Zhiming Luo Sheng Lian Shaozi Li OffRL 16 29 0 05 Nov 2018
Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms Thomas Gabor Lenz Belzner Thomy Phan Kyrill Schmid 19 14 0 30 Oct 2018
Predictive Uncertainty through Quantization Bastiaan S. Veeling Rianne van den Berg Max Welling UQCV 8 1 0 12 Oct 2018
Predicting Periodicity with Temporal Difference Learning Kristopher De Asis Brendan Bennett R. Sutton 14 1 0 20 Sep 2018
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN Dror Freirich Ron Meir Aviv Tamar OffRL 27 13 0 06 Aug 2018
Autoregressive Quantile Networks for Generative Modeling Georg Ostrovski Will Dabney Rémi Munos DRL 28 85 0 14 Jun 2018
Implicit Quantile Networks for Distributional Reinforcement Learning Will Dabney Georg Ostrovski David Silver Rémi Munos OffRL 13 529 0 14 Jun 2018
The Potential of the Return Distribution for Exploration in RL Thomas M. Moerland Joost Broekens Catholijn M. Jonker 29 9 0 11 Jun 2018
Distributional Advantage Actor-Critic Shangda Li Selina Bing Steven Yang OffRL 8 6 0 10 Jun 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 21 372 0 08 Jun 2018
Nonlinear Distributional Gradient Temporal-Difference Learning Chao Qu Shie Mannor Huan Xu 30 12 0 20 May 2018
An Analysis of Categorical Distributional Reinforcement Learning Mark Rowland Marc G. Bellemare Will Dabney Rémi Munos Yee Whye Teh 25 101 0 22 Feb 2018
Quantile Markov Decision Process Xiaocheng Li Huaiyang Zhong M. Brandeau 29 5 0 15 Nov 2017