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Visual Reinforcement Learning with Imagined Goals

12 July 2018

Papers citing "Visual Reinforcement Learning with Imagined Goals"

35 / 235 papers shown

Title
Language as an Abstraction for Hierarchical Deep Reinforcement Learning Yiding Jiang S. Gu Kevin Patrick Murphy Chelsea Finn OffRL 69 225 0 18 Jun 2019
Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards Gerrit Schoettler Ashvin Nair Jianlan Luo Shikhar Bahl J. A. Ojea Eugen Solowjow Sergey Levine OffRL 59 192 0 13 Jun 2019
Goal-conditioned Imitation Learning Yiming Ding Carlos Florensa Mariano Phielipp Pieter Abbeel 78 228 0 13 Jun 2019
Sub-policy Adaptation for Hierarchical Reinforcement Learning Alexander C. Li Carlos Florensa I. Clavera Pieter Abbeel 96 74 0 13 Jun 2019
Efficient Exploration via State Marginal Matching Lisa Lee Benjamin Eysenbach Emilio Parisotto Eric Xing Sergey Levine Ruslan Salakhutdinov 147 248 0 12 Jun 2019
Exploration via Hindsight Goal Generation Zhizhou Ren Kefan Dong Yuanshuo Zhou Qiang Liu Jian-wei Peng 85 90 0 10 Jun 2019
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset Muhammad Waleed Gondal Manuel Wüthrich Ðorðe Miladinovic Francesco Locatello M. Breidt V. Volchkov J. Akpo Olivier Bachem Bernhard Schölkopf Stefan Bauer OOD DRL 125 139 0 07 Jun 2019
On the Fairness of Disentangled Representations Francesco Locatello G. Abbati Tom Rainforth Stefan Bauer Bernhard Schölkopf Olivier Bachem FaML DRL 81 227 0 31 May 2019
Unsupervised Model Selection for Variational Disentangled Representation Learning Sunny Duan Loic Matthey Andre Saraiva Nicholas Watters Christopher P. Burgess Alexander Lerchner I. Higgins OOD DRL 96 80 0 29 May 2019
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning Rui Zhao Xudong Sun Volker Tresp 67 83 0 21 May 2019
Reinforcement Learning without Ground-Truth State Xingyu Lin H. Baweja David Held OffRL SSL 80 24 0 20 May 2019
REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning Brian Yang Jesse Zhang Vitchyr H. Pong Sergey Levine Dinesh Jayaraman 77 37 0 17 May 2019
Learning Robotic Manipulation through Visual Planning and Acting Angelina Wang Thanard Kurutach Kara Liu Pieter Abbeel Aviv Tamar 59 116 0 11 May 2019
Hierarchical Policy Learning is Sensitive to Goal Space Design Zach Dwiel Madhavun Candadai Mariano Phielipp Arjun K. Bansal 79 15 0 04 May 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 103 124 0 03 May 2019
Goal-Directed Behavior under Variational Predictive Coding: Dynamic Organization of Visual Attention and Working Memory Minju Jung Takazumi Matsumoto Jun Tani 69 20 0 12 Mar 2019
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning Vitchyr H. Pong Murtaza Dalal Steven Lin Ashvin Nair Shikhar Bahl Sergey Levine OffRL SSL 132 277 0 08 Mar 2019
Learning Latent Plans from Play Corey Lynch Mohi Khansari Ted Xiao Vikash Kumar Jonathan Tompson Sergey Levine P. Sermanet SSL LM&Ro 115 408 0 05 Mar 2019
Discovering Options for Exploration by Minimizing Cover Time Yuu Jinnai Jee Won Park David Abel George Konidaris 78 52 0 02 Mar 2019
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control Jeremy Morton F. Witherden Mykel J Kochenderfer 85 47 0 26 Feb 2019
Unsupervised Visuomotor Control through Distributional Planning Networks Tianhe Yu Gleb Shevchuk Dorsa Sadigh Chelsea Finn SSL OffRL 77 42 0 14 Feb 2019
Preferences Implicit in the State of the World Rohin Shah Dmitrii Krasheninnikov Jordan Alexander Pieter Abbeel Anca Dragan 82 55 0 12 Feb 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
VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control Xingxing Liang Qi Wang Yanghe Feng Zhong Liu Jincai Huang 65 5 0 24 Dec 2018
Variational Autoencoders Pursue PCA Directions (by Accident) Michal Rolínek Dominik Zietlow Georg Martius OOD DRL 78 153 0 17 Dec 2018
Provably Efficient Maximum Entropy Exploration Elad Hazan Sham Kakade Karan Singh A. V. Soest 98 305 0 06 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 166 1,475 0 29 Nov 2018
Unsupervised Control Through Non-Parametric Discriminative Rewards David Warde-Farley T. Wiele Tejas D. Kulkarni Catalin Ionescu Steven Hansen Volodymyr Mnih DRL OffRL SSL 101 178 0 28 Nov 2018
Learning Actionable Representations with Goal-Conditioned Policies Dibya Ghosh Abhishek Gupta Sergey Levine 102 110 0 19 Nov 2018
One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL T. Paine Sergio Gomez Colmenarejo Ziyun Wang Scott E. Reed Y. Aytar ... Matthew W. Hoffman Gabriel Barth-Maron Serkan Cabi David Budden Nando de Freitas OffRL 81 25 0 11 Oct 2018
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks Fabio Pardo Vitaly Levdik Petar Kormushev 57 4 0 06 Oct 2018
Time Reversal as Self-Supervision Suraj Nair Mohammad Babaeizadeh Chelsea Finn Sergey Levine Vikash Kumar SSL 89 12 0 02 Oct 2018
Catastrophic Importance of Catastrophic Forgetting Albert Ierusalem CLL AI4CE 18 2 0 20 Aug 2018
Automatically Composing Representation Transformations as a Means for Generalization Michael Chang Abhishek Gupta Sergey Levine Thomas Griffiths 85 70 0 12 Jul 2018
Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning Sébastien Forestier Rémy Portelas Yoan Mollard Pierre-Yves Oudeyer 99 190 0 07 Aug 2017