Temporal Difference Models: Model-Free Deep RL for Model-Based Control

25 February 2018

Papers citing "Temporal Difference Models: Model-Free Deep RL for Model-Based Control"

21 / 21 papers shown

Title
Online Reinforcement Learning in Non-Stationary Context-Driven Environments Pouya Hamadanian Arash Nasr-Esfahany Malte Schwarzkopf Siddartha Sen MohammadIman Alizadeh CLL OffRL 92 0 0 04 Feb 2023
Overcoming Model Bias for Robust Offline Deep Reinforcement Learning Phillip Swazinna Steffen Udluft Thomas Runkler OffRL 50 83 0 12 Aug 2020
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning Anusha Nagabandi G. Kahn R. Fearing Sergey Levine 81 967 0 08 Aug 2017
A Distributional Perspective on Reinforcement Learning Marc G. Bellemare Will Dabney Rémi Munos OffRL 82 1,497 0 21 Jul 2017
Hindsight Experience Replay Marcin Andrychowicz Dwight Crow Alex Ray Jonas Schneider Rachel Fong Peter Welinder Bob McGrew Joshua Tobin Pieter Abbeel Wojciech Zaremba OffRL 233 2,307 0 05 Jul 2017
Discrete Sequential Prediction of Continuous Actions for Deep RL Luke Metz Julian Ibarz Navdeep Jaitly James Davidson BDL OffRL 65 118 0 14 May 2017
Goal-Driven Dynamics Learning via Bayesian Optimization Somil Bansal Roberto Calandra Ted Xiao Sergey Levine Claire Tomlin 45 113 0 27 Mar 2017
Prediction and Control with Temporal Segment Models Nikhil Mishra Pieter Abbeel Igor Mordatch BDL 51 64 0 12 Mar 2017
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning Yevgen Chebotar Karol Hausman Marvin Zhang Gaurav Sukhatme S. Schaal Sergey Levine 63 160 0 08 Mar 2017
The Predictron: End-To-End Learning and Planning David Silver H. V. Hasselt Matteo Hessel Tom Schaul A. Guez ... Gabriel Dulac-Arnold David P. Reichert Neil C. Rabinowitz André Barreto T. Degris 52 289 0 28 Dec 2016
Reinforcement Learning with Unsupervised Auxiliary Tasks Max Jaderberg Volodymyr Mnih Wojciech M. Czarnecki Tom Schaul Joel Z Leibo David Silver Koray Kavukcuoglu SSL 62 1,225 0 16 Nov 2016
Learning to Act by Predicting the Future Alexey Dosovitskiy V. Koltun 132 280 0 06 Nov 2016
Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates S. Gu E. Holly Timothy Lillicrap Sergey Levine OffRL SSL 109 1,477 0 03 Oct 2016
Benchmarking Deep Reinforcement Learning for Continuous Control Yan Duan Xi Chen Rein Houthooft John Schulman Pieter Abbeel OffRL 76 1,689 0 22 Apr 2016
Continuous Deep Q-Learning with Model-based Acceleration S. Gu Timothy Lillicrap Ilya Sutskever Sergey Levine 69 1,010 0 02 Mar 2016
Learning Continuous Control Policies by Stochastic Value Gradients N. Heess Greg Wayne David Silver Timothy Lillicrap Yuval Tassa Tom Erez 95 560 0 30 Oct 2015
Learning Deep Control Policies for Autonomous Aerial Vehicles with MPC-Guided Policy Search Tianhao Zhang G. Kahn Sergey Levine Pieter Abbeel 65 427 0 22 Sep 2015
Continuous control with deep reinforcement learning Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel N. Heess Tom Erez Yuval Tassa David Silver Daan Wierstra 247 13,174 0 09 Sep 2015
End-to-End Training of Deep Visuomotor Policies Sergey Levine Chelsea Finn Trevor Darrell Pieter Abbeel BDL 251 3,418 0 02 Apr 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.1K 149,474 0 22 Dec 2014
Learning Parameterized Skills Bruno C. da Silva George Konidaris A. Barto 106 207 0 27 Jun 2012