Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning

19 July 2022

Ding Zhao

Papers citing "Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning"

26 / 26 papers shown

Title
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making Vivek Myers Chongyi Zheng Anca Dragan Sergey Levine Benjamin Eysenbach OffRL 84 9 0 24 Jun 2024
A Theory of Abstraction in Reinforcement Learning David Abel OffRL 29 29 0 01 Mar 2022
Abstraction for Deep Reinforcement Learning Murray Shanahan Melanie Mitchell OffRL 53 27 0 10 Feb 2022
Learning Domain Invariant Representations in Goal-conditioned Block MDPs Beining Han Chongyi Zheng Harris Chan Keiran Paster Michael Ruogu Zhang Jimmy Ba OOD AI4CE 45 13 0 27 Oct 2021
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 83 43 0 06 Sep 2021
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning Nan Rosemary Ke Aniket Didolkar Sarthak Mittal Anirudh Goyal Guillaume Lajoie Stefan Bauer Danilo Jimenez Rezende Yoshua Bengio Michael C. Mozer C. Pal CML 59 55 0 02 Jul 2021
Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation Nicklas Hansen H. Su Xiaolong Wang OffRL 72 136 0 01 Jul 2021
Learning Task Decomposition with Ordered Memory Policy Network Yucheng Lu Songlin Yang Siyuan Zhou Aaron Courville J. Tenenbaum Chuang Gan 36 15 0 19 Mar 2021
Model-Invariant State Abstractions for Model-Based Reinforcement Learning Manan Tomar Amy Zhang Roberto Calandra Matthew E. Taylor Joelle Pineau 43 24 0 19 Feb 2021
Goal-Aware Prediction: Learning to Model What Matters Suraj Nair Silvio Savarese Chelsea Finn 60 64 0 14 Jul 2020
Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning Qing Li Siyuan Huang Yining Hong Yixin Chen Ying Nian Wu Song-Chun Zhu NAI 53 83 0 11 Jun 2020
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels Ilya Kostrikov Denis Yarats Rob Fergus OffRL 75 784 0 28 Apr 2020
Resolving Spurious Correlations in Causal Models of Environments via Interventions S. Volodin Nevan Wichers Jeremy Nixon CML 26 16 0 12 Feb 2020
Causal Induction from Visual Observations for Goal Directed Tasks Sunjay Cauligi Yuke Zhu D. Stefan Tamara Rezk CML LRM 54 63 0 03 Oct 2019
Learning Neural Causal Models from Unknown Interventions Nan Rosemary Ke O. Bilaniuk Anirudh Goyal Stefan Bauer Hugo Larochelle Bernhard Schölkopf Michael C. Mozer C. Pal Yoshua Bengio CML OOD 82 168 0 02 Oct 2019
Regression Planning Networks Danfei Xu Roberto Martín-Martín De-An Huang Yuke Zhu Silvio Savarese Li Fei-Fei 29 57 0 28 Sep 2019
Benchmarking Model-Based Reinforcement Learning Tingwu Wang Xuchan Bao I. Clavera Jerrick Hoang Yeming Wen Eric D. Langlois Matthew Shunshi Zhang Guodong Zhang Pieter Abbeel Jimmy Ba OffRL 59 361 0 03 Jul 2019
Explainable Reinforcement Learning Through a Causal Lens Prashan Madumal Tim Miller L. Sonenberg F. Vetere CML 81 357 0 27 May 2019
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs D. Gilboa B. Chang Minmin Chen Greg Yang S. Schoenholz Ed H. Chi Jeffrey Pennington 63 41 0 25 Jan 2019
Experimental Design for Cost-Aware Learning of Causal Graphs Erik M. Lindgren Murat Kocaoglu A. Dimakis S. Vishwanath CML 38 37 0 28 Oct 2018
Structured Domain Randomization: Bridging the Reality Gap by Context-Aware Synthetic Data Aayush Prakash Shaad Boochoon M. Brophy David Acuna Eric Cameracci Gavriel State Omer Shapira Stan Birchfield 44 265 0 23 Oct 2018
Automatic Goal Generation for Reinforcement Learning Agents Carlos Florensa David Held Xinyang Geng Pieter Abbeel 100 506 0 17 May 2017
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World Joshua Tobin Rachel Fong Alex Ray Jonas Schneider Wojciech Zaremba Pieter Abbeel 189 2,948 0 20 Mar 2017
Modeling Relational Data with Graph Convolutional Networks Michael Schlichtkrull Thomas Kipf Peter Bloem Rianne van den Berg Ivan Titov Max Welling GNN 172 4,772 0 17 Mar 2017
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 361 12,662 0 11 Dec 2014
Kernel-based Conditional Independence Test and Application in Causal Discovery Kun Zhang J. Peters Dominik Janzing Bernhard Schölkopf BDL CML 82 618 0 14 Feb 2012