Combined Reinforcement Learning via Abstract Representations

12 September 2018

Vincent François-Lavet

Papers citing "Combined Reinforcement Learning via Abstract Representations"

22 / 22 papers shown

Title
Bridging State and History Representations: Understanding Self-Predictive RL Tianwei Ni Benjamin Eysenbach Erfan Seyedsalehi Michel Ma Clement Gehring Aditya Mahajan Pierre-Luc Bacon AI4TS AI4CE 22 20 0 17 Jan 2024
Disentangled (Un)Controllable Features Jacob E. Kooi Mark Hoogendoorn Vincent François-Lavet DRL 27 0 0 31 Oct 2022
Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning Jifeng Hu Yanchao Sun Hechang Chen Sili Huang Haiyin Piao Yi-Ju Chang Lichao Sun 15 5 0 14 Oct 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
Learning List-wise Representation in Reinforcement Learning for Ads Allocation with Multiple Auxiliary Tasks Zehua Wang Guogang Liao Xiaowen Shi Xiaoxu Wu Chuheng Zhang Yongkang Wang Xingxing Wang Dong Wang OffRL 19 4 0 02 Apr 2022
Factored Adaptation for Non-Stationary Reinforcement Learning Fan Feng Erdun Gao Kun Zhang Sara Magliacane CML OffRL 45 32 0 30 Mar 2022
elBERto: Self-supervised Commonsense Learning for Question Answering Xunlin Zhan Yuan Li Xiao Dong Xiaodan Liang Zhiting Hu Lawrence Carin SSL RALM LRM 24 7 0 17 Mar 2022
SAGE: Generating Symbolic Goals for Myopic Models in Deep Reinforcement Learning A. Chester Michael Dann Fabio Zambetta John Thangarajah 11 0 0 09 Mar 2022
Component Transfer Learning for Deep RL Based on Abstract Representations Geoffrey van Driessel Vincent François-Lavet DRL OffRL 28 6 0 22 Nov 2021
Reasoning-Modulated Representations Petar Velivcković Matko Bovsnjak Thomas Kipf Alexander Lerchner R. Hadsell Razvan Pascanu Charles Blundell OCL OOD SSL 13 15 0 19 Jul 2021
Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics N. Botteghi M. Poel B. Sirmaçek C. Brune 24 3 0 04 Jul 2021
MICo: Improved representations via sampling-based state similarity for Markov decision processes Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 43 35 0 03 Jun 2021
Learning First-Order Representations for Planning from Black-Box States: New Results I. D. Rodriguez Blai Bonet J. Romero Hector Geffner NAI 17 21 0 23 May 2021
Combining Planning and Learning of Behavior Trees for Robotic Assembly Jonathan Styrud Matteo Iovino M. Norrlöf Mårten Björkman Christian Smith 37 40 0 16 Mar 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
Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review Rongrong Liu F. Nageotte P. Zanne M. de Mathelin Birgitta Dresp 48 143 0 08 Feb 2021
Novelty Search in Representational Space for Sample Efficient Exploration Ruo Yu Tao Vincent François-Lavet Joelle Pineau 30 43 0 28 Sep 2020
State Action Separable Reinforcement Learning Ziyao Zhang Liang Ma K. Leung Konstantinos Poularakis M. Srivatsa 31 2 0 05 Jun 2020
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning Z. Guo Bernardo Avila-Pires Bilal Piot Jean-Bastien Grill Florent Altché Rémi Munos M. G. Azar BDL DRL SSL 43 139 0 30 Apr 2020
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models Arunkumar Byravan Jost Tobias Springenberg A. Abdolmaleki Roland Hafner Michael Neunert Thomas Lampe Noah Y. Siegel N. Heess Martin Riedmiller OffRL 11 41 0 09 Oct 2019
Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning Lucas Lehnert Michael L. Littman 8 10 0 31 Jan 2019
Reward Estimation for Variance Reduction in Deep Reinforcement Learning Joshua Romoff Peter Henderson Alexandre Piché Vincent François-Lavet Joelle Pineau 6 42 0 09 May 2018