A Geometric Perspective on Optimal Representations for Reinforcement Learning

31 January 2019

Nicolas Le Roux

Papers citing "A Geometric Perspective on Optimal Representations for Reinforcement Learning"

30 / 30 papers shown

Title
Physics-informed Temporal Difference Metric Learning for Robot Motion Planning Ruiqi Ni Zherong Pan A. H. Qureshi SSL 39 0 0 09 May 2025
Disentangling Recognition and Decision Regrets in Image-Based Reinforcement Learning Alihan Hüyük A. R. Koblitz Atefeh Mohajeri M. Andrews OffRL 40 0 0 19 Sep 2024
A Role of Environmental Complexity on Representation Learning in Deep Reinforcement Learning Agents Andrew Liu Alla Borisyuk 32 1 0 03 Jul 2024
Graph Neural Thompson Sampling Shuang Wu Arash A. Amini 51 0 0 15 Jun 2024
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 38 4 0 05 Oct 2023
Online Network Source Optimization with Graph-Kernel MAB Laura Toni P. Frossard 26 1 0 07 Jul 2023
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions Nishil Patel Sebastian Lee Stefano Sarao Mannelli Sebastian Goldt Adrew Saxe OffRL 28 3 0 17 Jun 2023
VIBR: Learning View-Invariant Value Functions for Robust Visual Control Tom Dupuis Jaonary Rabarisoa Q. C. Pham David Filliat 36 0 0 14 Jun 2023
Towards a Better Understanding of Representation Dynamics under TD-learning Yunhao Tang Rémi Munos OffRL 26 1 0 29 May 2023
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning Tongzhou Wang Antonio Torralba Phillip Isola Amy Zhang OffRL 32 31 0 03 Apr 2023
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces Charline Le Lan Joshua Greaves Jesse Farebrother Mark Rowland Fabian Pedregosa Rishabh Agarwal Marc G. Bellemare 52 8 0 08 Dec 2022
On learning history based policies for controlling Markov decision processes Gandharv Patil Aditya Mahajan Doina Precup OffRL 21 5 0 06 Nov 2022
A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning Guozheng Ma Zhen Wang Zhecheng Yuan Xueqian Wang Bo Yuan Dacheng Tao OffRL 38 26 0 10 Oct 2022
Sparsity Inducing Representations for Policy Decompositions Ashwin Khadke H. Geyer 16 1 0 15 Sep 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning Shuang Qiu Lingxiao Wang Chenjia Bai Zhuoran Yang Zhaoran Wang SSL OffRL 26 32 0 29 Jul 2022
Geometric Policy Iteration for Markov Decision Processes Yue Wu J. D. Loera 26 3 0 12 Jun 2022
Understanding and Preventing Capacity Loss in Reinforcement Learning Clare Lyle Mark Rowland Will Dabney CLL 36 109 0 20 Apr 2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach Xuezhou Zhang Yuda Song Masatoshi Uehara Mengdi Wang Alekh Agarwal Wen Sun OffRL 29 57 0 31 Jan 2022
The Geometry of Robust Value Functions Kaixin Wang Navdeep Kumar Kuangqi Zhou Bryan Hooi Jiashi Feng Shie Mannor AAML 27 7 0 30 Jan 2022
Transfer RL across Observation Feature Spaces via Model-Based Regularization Yanchao Sun Ruijie Zheng Xiyao Wang Andrew Cohen Furong Huang OOD OffRL 22 21 0 01 Jan 2022
The Information Geometry of Unsupervised Reinforcement Learning Benjamin Eysenbach Ruslan Salakhutdinov Sergey Levine SSL OffRL 61 31 0 06 Oct 2021
Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits Simon Ståhlberg Blai Bonet Hector Geffner 41 48 0 21 Sep 2021
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research Chris Cummins Bram Wasti Jiadong Guo Brandon Cui Jason Ansel ... Jia-Wei Liu O. Teytaud Benoit Steiner Yuandong Tian Hugh Leather 31 68 0 17 Sep 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? Kate Rakelly Abhishek Gupta Carlos Florensa Sergey Levine SSL 26 38 0 14 Jun 2021
Return-Based Contrastive Representation Learning for Reinforcement Learning Guoqing Liu Chuheng Zhang Li Zhao Tao Qin Jinhua Zhu Jian Li Nenghai Yu Tie-Yan Liu SSL OffRL 11 47 0 22 Feb 2021
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey Chongzhen Zhang Jianrui Wang Gary G. Yen Chaoqiang Zhao Qiyu Sun Yang Tang Feng Qian Jürgen Kurths AAML 31 20 0 29 Mar 2020
Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey Yang Tang Chaoqiang Zhao Jianrui Wang Chongzhen Zhang Qiyu Sun Weixing Zheng W. Du Feng Qian Jürgen Kurths 18 65 0 08 Jan 2020
Learning Representations in Reinforcement Learning:An Information Bottleneck Approach Yingjun Pei Xinwen Hou SSL 31 10 0 12 Nov 2019
Discovery of Useful Questions as Auxiliary Tasks Vivek Veeriah Matteo Hessel Zhongwen Xu Richard L. Lewis Janarthanan Rajendran Junhyuk Oh H. V. Hasselt David Silver Satinder Singh LLMAG 14 86 0 10 Sep 2019
A Survey and Critique of Multiagent Deep Reinforcement Learning Pablo Hernandez-Leal Bilal Kartal Matthew E. Taylor OffRL 32 550 0 12 Oct 2018