Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion

4 July 2018

Papers citing "Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion"

47 / 97 papers shown

Title
Deep Reinforcement Learning with Adjustments H. Khorasgani Haiyan Wang Chetan Gupta Susumu Serita 23 2 0 28 Sep 2021
When should agents explore? Miruna Pislar David Szepesvari Georg Ostrovski Diana Borsa Tom Schaul 40 22 0 26 Aug 2021
Visual Adversarial Imitation Learning using Variational Models Rafael Rafailov Tianhe Yu Aravind Rajeswaran Chelsea Finn SSL 30 49 0 16 Jul 2021
Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research J. Luis E. Crawley B. Cameron OffRL 27 6 0 07 Jul 2021
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction Assaf Hallak Gal Dalal Steven Dalton I. Frosio Shie Mannor Gal Chechik OffRL OnRL 35 9 0 04 Jul 2021
MHER: Model-based Hindsight Experience Replay Rui Yang Meng Fang Lei Han Yali Du Feng Luo Xiu Li OffRL 29 17 0 01 Jul 2021
Offline Reinforcement Learning as One Big Sequence Modeling Problem Michael Janner Qiyang Li Sergey Levine OffRL 71 651 0 03 Jun 2021
MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks Menghui Zhu Minghuan Liu Jian Shen Zhicheng Zhang Sheng Chen Weinan Zhang Deheng Ye Yong Yu Qiang Fu Wei Yang 49 22 0 13 May 2021
Principled Exploration via Optimistic Bootstrapping and Backward Induction Chenjia Bai Lingxiao Wang Lei Han Jianye Hao Animesh Garg Peng Liu Zhaoran Wang OffRL 23 38 0 13 May 2021
Learning to drive from a world on rails Di Chen V. Koltun Philipp Krahenbuhl 98 116 0 03 May 2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills Yevgen Chebotar Karol Hausman Yao Lu Ted Xiao Dmitry Kalashnikov ... A. Irpan Benjamin Eysenbach Ryan Julian Chelsea Finn Sergey Levine SSL OffRL 37 146 0 15 Apr 2021
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow John Mcleod Hrvoje Stojić Vincent Adam Dongho Kim Jordi Grau-Moya Peter Vrancx Felix Leibfried OffRL 21 2 0 26 Mar 2021
GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning Juhyoung Lee Sangyeob Kim Sangjin Kim Wooyoung Jo H. Yoo OffRL 26 9 0 24 Jan 2021
A Survey on Deep Reinforcement Learning for Audio-Based Applications S. Latif Heriberto Cuayáhuitl Farrukh Pervez Fahad Shamshad Hafiz Shehbaz Ali Min Zhang OffRL 60 73 0 01 Jan 2021
Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation Chaochao Lu Erdun Gao Ke Wang José Miguel Hernández-Lobato Kun Zhang Bernhard Schölkopf CML OOD OffRL 29 57 0 16 Dec 2020
Generative Temporal Difference Learning for Infinite-Horizon Prediction Michael Janner Igor Mordatch Sergey Levine AI4CE 23 34 0 27 Oct 2020
Model-based Policy Optimization with Unsupervised Model Adaptation Jian Shen Han Zhao Weinan Zhang Yong Yu 34 27 0 19 Oct 2020
Softmax Deep Double Deterministic Policy Gradients Ling Pan Qingpeng Cai Longbo Huang 72 86 0 19 Oct 2020
Mastering Atari with Discrete World Models Danijar Hafner Timothy Lillicrap Mohammad Norouzi Jimmy Ba DRL 53 823 0 05 Oct 2020
Dynamic Horizon Value Estimation for Model-based Reinforcement Learning Junjie Wang Qichao Zhang Dongbin Zhao Mengchen Zhao Jianye Hao OffRL 29 5 0 21 Sep 2020
Systematic Generalization on gSCAN with Language Conditioned Embedding Tong Gao Qi Huang Raymond J. Mooney 24 22 0 11 Sep 2020
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems Sandhya Saisubramanian S. Zilberstein Ece Kamar 20 21 0 24 Aug 2020
Learning Off-Policy with Online Planning Harshit S. Sikchi Wenxuan Zhou David Held OffRL 37 46 0 23 Aug 2020
Selective Dyna-style Planning Under Limited Model Capacity Zaheer Abbas Samuel Sokota Erin J. Talvitie Martha White 37 32 0 05 Jul 2020
A Unifying Framework for Reinforcement Learning and Planning Thomas M. Moerland Joost Broekens Aske Plaat Catholijn M. Jonker OffRL 36 9 0 26 Jun 2020
The Effect of Multi-step Methods on Overestimation in Deep Reinforcement Learning Lingheng Meng R. Gorbet Dana Kulic OffRL 30 27 0 23 Jun 2020
Model-based Adversarial Meta-Reinforcement Learning Zichuan Lin G. Thomas Guangwen Yang Tengyu Ma OOD 27 52 0 16 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 33 82 0 15 Jun 2020
Variational Model-based Policy Optimization Yinlam Chow Brandon Cui Moonkyung Ryu Mohammad Ghavamzadeh OffRL 22 12 0 09 Jun 2020
Maximum Entropy Model Rollouts: Fast Model Based Policy Optimization without Compounding Errors Chi Zhang S. Kuppannagari Viktor Prasanna 22 4 0 08 Jun 2020
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals Henry Charlesworth Giovanni Montana OffRL 29 24 0 01 Jun 2020
Model-Augmented Actor-Critic: Backpropagating through Paths I. Clavera Yao Fu Pieter Abbeel 44 87 0 16 May 2020
An empirical investigation of the challenges of real-world reinforcement learning Gabriel Dulac-Arnold Nir Levine D. Mankowitz Jerry Li Cosmin Paduraru Sven Gowal Todd Hester OffRL 34 121 0 24 Mar 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 38 314 0 15 Feb 2020
Direct and indirect reinforcement learning Yang Guan Shengbo Eben Li Jingliang Duan Jie Li Yangang Ren Qi Sun B. Cheng OffRL 38 34 0 23 Dec 2019
Combining Q-Learning and Search with Amortized Value Estimates Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez Tobias Pfaff T. Weber Lars Buesing Peter W. Battaglia OffRL 27 47 0 05 Dec 2019
Adaptive Online Planning for Continual Lifelong Learning Kevin Lu Igor Mordatch Pieter Abbeel OffRL OnRL CLL 11 15 0 03 Dec 2019
Multi-Path Policy Optimization L. Pan Qingpeng Cai Longbo Huang 18 2 0 11 Nov 2019
Asynchronous Methods for Model-Based Reinforcement Learning Yunzhi Zhang I. Clavera Bo-Yu Tsai Pieter Abbeel OffRL 19 27 0 28 Oct 2019
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles Aditya Modi Nan Jiang Ambuj Tewari Satinder Singh 30 129 0 23 Oct 2019
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 17 41 0 09 Oct 2019
Soft-Label Dataset Distillation and Text Dataset Distillation Ilia Sucholutsky Matthias Schonlau DD 33 132 0 06 Oct 2019
Gradient-Aware Model-based Policy Search P. DÓro Alberto Maria Metelli Andrea Tirinzoni Matteo Papini Marcello Restelli 29 34 0 09 Sep 2019
Deterministic Value-Policy Gradients Qingpeng Cai L. Pan Pingzhong Tang 29 1 0 09 Sep 2019
Sample-efficient Deep Reinforcement Learning with Imaginary Rollouts for Human-Robot Interaction M. Thabet Massimiliano Patacchiola Angelo Cangelosi OffRL 24 12 0 15 Aug 2019
Towards Model-based Reinforcement Learning for Industry-near Environments Per-Arne Andersen M. G. Olsen Ole-Christoffer Granmo OffRL DRL 22 4 0 27 Jul 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015