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Successor Features for Transfer in Reinforcement Learning

16 June 2016

David Silver

Papers citing "Successor Features for Transfer in Reinforcement Learning"

50 / 203 papers shown

Title
A neurally plausible model learns successor representations in partially observable environments Eszter Vértes M. Sahani 55 43 0 22 Jun 2019
Shaping Belief States with Generative Environment Models for RL Karol Gregor Danilo Jimenez Rezende F. Besse Yan Wu Hamza Merzic Aaron van den Oord OffRL AI4CE 129 119 0 21 Jun 2019
Better transfer learning with inferred successor maps T. Madarász 87 22 0 18 Jun 2019
Fast Task Inference with Variational Intrinsic Successor Features Steven Hansen Will Dabney André Barreto T. Wiele David Warde-Farley Volodymyr Mnih BDL 100 152 0 12 Jun 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning Carles Gelada Saurabh Kumar Jacob Buckman Ofir Nachum Marc G. Bellemare BDL 93 288 0 06 Jun 2019
Reinforcement Learning Experience Reuse with Policy Residual Representation Wen-Ji Zhou Yang Yu Yingfeng Chen Kai Guan Tangjie Lv Changjie Fan Zhi Zhou OffRL 19 2 0 31 May 2019
Task-Agnostic Dynamics Priors for Deep Reinforcement Learning Yilun Du Karthik Narasimhan 87 33 0 13 May 2019
Truly Batch Apprenticeship Learning with Deep Successor Features Donghun Lee Srivatsan Srinivasan Finale Doshi-Velez OffRL OOD 74 36 0 24 Mar 2019
Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration Jingwei Zhang Niklas Wetzel Nicolai Dorka Joschka Boedecker Wolfram Burgard 65 26 0 18 Mar 2019
Model Primitive Hierarchical Lifelong Reinforcement Learning Bohan Wu Jayesh K. Gupta Mykel J. Kochenderfer OffRL 45 10 0 04 Mar 2019
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies Tom Zahavy Avinatan Hassidim Haim Kaplan Yishay Mansour OffRL 77 7 0 26 Feb 2019
Source Traces for Temporal Difference Learning Silviu Pitis 63 16 0 08 Feb 2019
Distilling Policy Distillation Wojciech M. Czarnecki Razvan Pascanu Simon Osindero Siddhant M. Jayakumar G. Swirszcz Max Jaderberg 83 134 0 06 Feb 2019
A Geometric Perspective on Optimal Representations for Reinforcement Learning Marc G. Bellemare Will Dabney Robert Dadashi Adrien Ali Taïga Pablo Samuel Castro Nicolas Le Roux Dale Schuurmans Tor Lattimore Clare Lyle 65 90 0 31 Jan 2019
Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning Lucas Lehnert Michael L. Littman 103 10 0 31 Jan 2019
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement André Barreto Diana Borsa John Quan Tom Schaul David Silver Matteo Hessel D. Mankowitz Augustin Žídek Rémi Munos OffRL 117 165 0 30 Jan 2019
Benchmarking Classic and Learned Navigation in Complex 3D Environments Dmytro Mishkin Alexey Dosovitskiy V. Koltun 137 75 0 30 Jan 2019
Self-supervised Learning of Image Embedding for Continuous Control Carlos Florensa Jonas Degrave N. Heess Jost Tobias Springenberg Martin Riedmiller SSL 58 53 0 03 Jan 2019
Universal Successor Features Approximators Diana Borsa André Barreto John Quan D. Mankowitz Rémi Munos H. V. Hasselt David Silver Tom Schaul 89 117 0 18 Dec 2018
Target Driven Visual Navigation with Hybrid Asynchronous Universal Successor Representations Shamane Siriwardhana Abdenacer Naouri Huansheng Ning 26 5 0 27 Nov 2018
Learning Actionable Representations with Goal-Conditioned Policies Dibya Ghosh Abhishek Gupta Sergey Levine 102 110 0 19 Nov 2018
Self-Organizing Maps for Storage and Transfer of Knowledge in Reinforcement Learning Thommen George Karimpanal Roland Bouffanais 53 55 0 18 Nov 2018
Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation G. Kahn Adam R. Villaflor Pieter Abbeel Sergey Levine SSL OffRL 82 19 0 16 Oct 2018
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning David Janz Jiri Hron Przemysław Mazur Katja Hofmann José Miguel Hernández-Lobato Sebastian Tschiatschek 163 52 0 15 Oct 2018
Deep Reinforcement Learning Yuxi Li VLM OffRL 194 144 0 15 Oct 2018
M $^3$ RL: Mind-aware Multi-agent Management Reinforcement Learning Tianmin Shu Yuandong Tian 92 54 0 29 Sep 2018
Target Transfer Q-Learning and Its Convergence Analysis Yue Wang Qi Meng Wei Cheng Yuting Liu Zhiming Ma Tie-Yan Liu 51 31 0 21 Sep 2018
Dynamic Weights in Multi-Objective Deep Reinforcement Learning Axel Abels D. Roijers Tom Lenaerts A. Nowé Denis Steckelmacher OffRL 85 163 0 20 Sep 2018
Fully Distributed Multi-Robot Collision Avoidance via Deep Reinforcement Learning for Safe and Efficient Navigation in Complex Scenarios Tingxiang Fan Pinxin Long Wenxi Liu Jia Pan 65 69 0 11 Aug 2018
Count-Based Exploration with the Successor Representation Marlos C. Machado Marc G. Bellemare Michael Bowling 63 189 0 31 Jul 2018
Transfer with Model Features in Reinforcement Learning Lucas Lehnert Michael L. Littman 23 10 0 04 Jul 2018
RUDDER: Return Decomposition for Delayed Rewards Jose A. Arjona-Medina Michael Gillhofer Michael Widrich Thomas Unterthiner Johannes Brandstetter Sepp Hochreiter 130 222 0 20 Jun 2018
Context-Aware Policy Reuse Siyuan Li Fangda Gu Guangxiang Zhu Chongjie Zhang OffRL 159 37 0 11 Jun 2018
Spectral Inference Networks: Unifying Deep and Spectral Learning David Pfau Stig Petersen Ashish Agarwal David Barrett Kimberly L. Stachenfeld 122 40 0 06 Jun 2018
Constrained Policy Improvement for Safe and Efficient Reinforcement Learning Elad Sarafian Aviv Tamar Sarit Kraus OffRL 60 11 0 20 May 2018
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications Daniel S. Brown S. Niekum OffRL 102 82 0 20 May 2018
Decoupling Dynamics and Reward for Transfer Learning Amy Zhang Harsh Satija Joelle Pineau OOD 78 72 0 27 Apr 2018
An Adaptive Clipping Approach for Proximal Policy Optimization Gang Chen Yiming Peng Mengjie Zhang 57 22 0 17 Apr 2018
Universal Successor Representations for Transfer Reinforcement Learning Chen Ma Junfeng Wen Yoshua Bengio OffRL 42 33 0 11 Apr 2018
Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation Craig Sherstan Marlos C. Machado P. Pilarski 67 10 0 23 Mar 2018
Learning by Playing - Solving Sparse Reward Tasks from Scratch Martin Riedmiller Roland Hafner Thomas Lampe Michael Neunert Jonas Degrave T. Wiele Volodymyr Mnih N. Heess Jost Tobias Springenberg 113 450 0 28 Feb 2018
Unicorn: Continual Learning with a Universal, Off-policy Agent D. Mankowitz Augustin Žídek André Barreto Dan Horgan Matteo Hessel John Quan Junhyuk Oh H. V. Hasselt David Silver Tom Schaul CLL OffRL 70 48 0 22 Feb 2018
Eigenoption Discovery through the Deep Successor Representation Marlos C. Machado Clemens Rosenbaum Xiaoxiao Guo Miao Liu Gerald Tesauro Murray Campbell 105 142 0 30 Oct 2017
An Optimal Online Method of Selecting Source Policies for Reinforcement Learning Siyuan Li Chongjie Zhang OnRL 59 44 0 24 Sep 2017
Decoupled Learning of Environment Characteristics for Safe Exploration Pieter Van Molle Tim Verbelen Steven Bohez Sam Leroux Pieter Simoens Bart Dhoedt OffRL 21 1 0 09 Aug 2017
Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning Lucas Lehnert Stefanie Tellex Michael L. Littman 79 49 0 31 Jul 2017
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning I. Higgins Arka Pal Andrei A. Rusu Loic Matthey Christopher P. Burgess Alexander Pritzel M. Botvinick Charles Blundell Alexander Lerchner DRL 163 418 0 26 Jul 2017
Visual Semantic Planning using Deep Successor Representations Yuke Zhu Daniel Gordon Eric Kolve Dieter Fox Li Fei-Fei Abhinav Gupta Roozbeh Mottaghi Ali Farhadi 103 142 0 23 May 2017
Faster Reinforcement Learning Using Active Simulators V. Jain Theja Tulabandhula 46 4 0 22 Mar 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 346 1,549 0 25 Jan 2017