Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control

Type: Preprint

Publication Date: 2018-11-05

Citations: 62

View

Locations

  • arXiv (Cornell University) - View

Similar Works

Action Title Year Authors
+ Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control 2018 Kendall Lowrey
Aravind Rajeswaran
Sham M. Kakade
Emanuel Todorov
Igor Mordatch
+ COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL 2023 Xiyao Wang
Ruijie Zheng
Yanchao Sun
Ruonan Jia
Wichayaporn Wongkamjan
Huazhe Xu
Furong Huang
+ Blending MPC & Value Function Approximation for Efficient Reinforcement Learning 2020 Mohak Bhardwaj
Sanjiban Choudhury
Byron Boots
+ Blending MPC & Value Function Approximation for Efficient Reinforcement Learning 2020 Mohak Bhardwaj
Sanjiban Choudhury
Byron Boots
+ Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning 2020 Michelle A. Lee
Carlos Florensa
Jonathan Tremblay
Nathan Ratliff
Animesh Garg
Fábio Ramos
Dieter Fox
+ Exploration via Planning for Information about the Optimal Trajectory 2022 Viraj Mehta
Ian Char
Joseph Abbate
Rory Conlin
Mark D. Boyer
Stefano Ermon
Jeff Schneider
Willie Neiswanger
+ Improving Model-Based Control and Active Exploration with Reconstruction Uncertainty Optimization 2018 Norman Di Palo
Harri Valpola
+ Model-Based Offline Planning 2020 Arthur Argenson
Gabriel Dulac-Arnold
+ PDF Chat Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning 2020 Michelle A. Lee
Carlos Florensa
Jonathan Tremblay
Nathan Ratliff
Animesh Garg
Fábio Ramos
Dieter Fox
+ Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning 2020 Michelle A. Lee
Carlos Florensa
Jonathan Tremblay
Nathan Ratliff
Animesh Garg
Fábio Ramos
Dieter Fox
+ A survey on policy search algorithms for learning robot controllers in a handful of trials 2018 Konstantinos Chatzilygeroudis
Vassilis Vassiliades
Freek Stulp
Sylvain Calinon
Jean-Baptiste Mouret
+ Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics 2021 Ingmar Schubert
Danny Driess
Ozgur S. Oguz
Marc Toussaint
+ PDF Chat Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics 2021 Ingmar Schubert
Danny Driess
Ozgur S. Oguz
Marc Toussaint
+ Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics 2021 Ingmar Schubert
Danny Driess
Ozgur S. Oguz
Marc Toussaint
+ Model-Based Offline Planning 2020 Arthur Argenson
Gabriel Dulac-Arnold
+ Model-based Lookahead Reinforcement Learning 2019 Zhang-Wei Hong
Joni Pajarinen
Jan Peters
+ LVIS: Learning from Value Function Intervals for Contact-Aware Robot Controllers 2018 Robin Deits
Twan Koolen
Russ Tedrake
+ LVIS: Learning from Value Function Intervals for Contact-Aware Robot Controllers 2018 Robin Deits
Twan Koolen
Russ Tedrake
+ Regularizing Model-Based Planning with Energy-Based Models 2019 Rinu Boney
Juho Kannala
Alexander Ilin
+ Model Learning for Look-ahead Exploration in Continuous Control 2018 Arpit Agarwal
Katharina Muelling
Katerina Fragkiadaki

Cited by (52)

Action Title Year Authors
+ Deep Dynamics Models for Learning Dexterous Manipulation 2019 Anusha Nagabandi
Kurt Konoglie
Sergey Levine
Vikash Kumar
+ Model-Augmented Actor-Critic: Backpropagating through Paths 2020 Ignasi Clavera
Violet Fu
Pieter Abbeel
+ Safe Interactive Model-Based Learning 2019 Marco Gallieri
Seyed Sina Mirrazavi Salehian
Nihat Engin Toklu
Alessio Quaglino
Jonathan Masci
Jan Koutník
Faustino Gomez
+ Learning Physics-Based Manipulation in Clutter: Combining Image-Based Generalization and Look-Ahead Planning 2019 Wissam Bejjani
Mehmet R. Doğar
Matteo Leonetti
+ PDF Chat Learning Physics-Based Manipulation in Clutter: Combining Image-Based Generalization and Look-Ahead Planning 2019 Wissam Bejjani
Mehmet R. Doğar
Matteo Leonetti
+ Improving Model-Based Control and Active Exploration with Reconstruction Uncertainty Optimization 2018 Norman Di Palo
Harri Valpola
+ Multi-Objective Graph Heuristic Search for Terrestrial Robot Design 2021 Jie Xu
Andrew Spielberg
Allan Zhao
Daniela Rus
Wojciech Matusik
+ AI and Wargaming 2020 James Goodman
Sebastian Risi
Simon M. Lucas
+ Planning to Explore via Self-Supervised World Models 2020 R. Sekar
Oleh Rybkin
Kostas Daniilidis
Pieter Abbeel
Danijar Hafner
Deepak Pathak
+ PDF Chat Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Control 2020 Yuan Lin
John McPhee
Nasser L. Azad
+ Learning Off-Policy with Online Planning 2020 Harshit Sikchi
Wenxuan Zhou
David Held
+ Regularizing Trajectory Optimization with Denoising Autoencoders 2019 Rinu Boney
Norman Di Palo
Mathias Berglund
Alexander Ilin
Juho Kannala
Antti Rasmus
Harri Valpola
+ Project Thyia: A Forever Gameplayer 2019 Raluca D. Gaina
Simon M. Lucas
Diego Pérez-Liébana
+ Discriminator Augmented Model-Based Reinforcement Learning 2021 Behzad Haghgoo
Allan Zhou
Archit Sharma
Chelsea Finn
+ ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions 2020 Brijen Thananjeyan
Ashwin Balakrishna
Ugo Rosolia
Joseph E. Gonzalez
Aaron D. Ames
Ken Goldberg
+ Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians 2021 Bruno Brito
Michael Everett
Jonathan P. How
Javier Alonso‐Mora
+ Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs 2020 Jianzhun Du
Joseph Futoma
Finale Doshi‐Velez
+ Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning 2022 Jinxin Liu
Donglin Wang
Qiangxing Tian
Zhengyu Chen
+ From proprioception to long-horizon planning in novel environments: A hierarchical RL model. 2020 Nishad Gothoskar
Miguel Lázaro-Gredilla
Dileep George
+ PDF Chat Multi-Objective Graph Heuristic Search for Terrestrial Robot Design 2021 Jie Xu
Andrew Spielberg
Allan Zhao
Daniela Rus
Wojciech Matusik
+ Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration 2021 Oliver Groth
Markus Wulfmeier
Giulia Vezzani
Vibhavari Dasagi
Tim Hertweck
Roland Hafner
Nicolas Heess
Martin Riedmiller
+ PDF Chat Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks 2020 Brijen Thananjeyan
Ashwin Balakrishna
Ugo Rosolia
Felix Li
Rowan McAllister
Joseph E. Gonzalez
Sergey Levine
Francesco Borrelli
Ken Goldberg
+ Dream to Control: Learning Behaviors by Latent Imagination 2019 Danijar Hafner
Timothy Lillicrap
Jimmy Ba
Mohammad Norouzi
+ Safe Model-Based Off-Policy Reinforcement Learning for Eco-Driving in Connected and Automated Hybrid Electric Vehicles 2022 Zhaoxuan Zhu
Nicola Pivaro
Shobhit Gupta
Abhishek Gupta
Marcello Canova
+ Safely Learning Dynamical Systems from Short Trajectories 2020 Amir Ali Ahmadi
Abraar Chaudhry
Vikas Sindhwani
Stephen Tu
+ Self-Adapting Recurrent Models for Object Pushing from Learning in Simulation 2020 Cong Lin
Michael Görner
Philipp Ruppel
Hongzhuo Liang
Norman Hendrich
Jianwei Zhang
+ Blending MPC & Value Function Approximation for Efficient Reinforcement Learning 2020 Mohak Bhardwaj
Sanjiban Choudhury
Byron Boots
+ Continuous Control With Ensemble Deep Deterministic Policy Gradients 2021 Piotr Januszewski
Mateusz Olko
Michał Królikowski
Jakub Świątkowski
Marcin Andrychowicz
Łukasz Kuciński
Piotr Miłoś
+ Optimization of the model predictive control meta-parameters through reinforcement learning 2023 Eivind Bøhn
Sébastien Gros
Signe Moe
Tor Arne Johansen
+ PDF Chat Mini Cheetah, the Falling Cat: A Case Study in Machine Learning and Trajectory Optimization for Robot Acrobatics 2022 Vince Kurtz
He Li
Patrick M. Wensing
Hai Lin
+ Reinforcement Learning of the Prediction Horizon in Model Predictive Control 2021 Eivind Bøhn
Sébastien Gros
Signe Moe
Tor Arne Johansen
+ Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning 2021 Andrew S. Morgan
Daljeet Nandha
Georgia Chalvatzaki
Carlo D’Eramo
Aaron M. Dollar
Jan Peters
+ Disentangled Attention as Intrinsic Regularization for Bimanual Multi-Object Manipulation. 2021 Minghao Zhang
Pingcheng Jian
Yi Wu
Huazhe Xu
Xiaolong Wang
+ A novel approach to model exploration for value function learning 2019 Zlatan Ajanović
Halil Beglerovic
Bakir Lačević
+ Information Theoretic Regret Bounds for Online Nonlinear Control 2020 Sham M. Kakade
Akshay Krishnamurthy
Kendall Lowrey
Motoya Ohnishi
W. Sun
+ Information Theoretic Model Predictive Q-Learning 2020 Mohak Bhardwaj
Ankur Handa
Dieter Fox
Byron Boots
+ Dream to Control: Learning Behaviors by Latent Imagination. 2019 Danijar Hafner
Timothy Lillicrap
Jimmy Ba
Mohammad Norouzi
+ PDF Chat Self-Adapting Recurrent Models for Object Pushing from Learning in Simulation 2020 Cong Lin
Michael Grner
Philipp Ruppel
Hongzhuo Liang
Norman Hendrich
Jianwei Zhang
+ PDF Chat Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner 2022 Philémon Brakel
Steven Bohez
Leonard Hasenclever
Nicolas Heess
Konstantinos Bousmalis
+ Reset-Free Lifelong Learning with Skill-Space Planning 2020 Kevin Lü
Aditya Grover
Pieter Abbeel
Igor Mordatch

Citing (18)

Action Title Year Authors
+ High-Dimensional Continuous Control Using Generalized Advantage Estimation 2015 John Schulman
Philipp Moritz
Sergey Levine
Michael I. Jordan
Pieter Abbeel
+ PDF Chat A contextual-bandit approach to personalized news article recommendation 2010 Lihong Li
Wei Chu
John Langford
Robert E. Schapire
+ VIME: Variational Information Maximizing Exploration 2016 Rein Houthooft
Xi Chen
Yan Duan
John Schulman
Filip De Turck
Pieter Abbeel
+ Unifying Count-Based Exploration and Intrinsic Motivation 2016 Marc G. Bellemare
Sriram Srinivasan
Georg Ostrovski
Tom Schaul
David Saxton
Rémi Munos
+ Curiosity-driven Exploration by Self-supervised Prediction 2017 Deepak Pathak
Pulkit Agrawal
Alexei A. Efros
Trevor Darrell
+ Thinking Fast and Slow with Deep Learning and Tree Search 2017 Thomas Anthony
Tian Zheng
David Barber
+ Parameter Space Noise for Exploration 2017 Matthias Plappert
Rein Houthooft
Prafulla Dhariwal
Szymon Sidor
Richard Y. Chen
Xi Chen
Tamim Asfour
Pieter Abbeel
Marcin Andrychowicz
+ Noisy Networks for Exploration 2017 Meire Fortunato
Mohammad Gheshlaghi Azar
Bilal Piot
Jacob Menick
Ian Osband
Alex Graves
Vlad Mnih
Rémi Munos
Demis Hassabis
Olivier Pietquin
+ Universal Planning Networks 2018 Aravind Srinivas
Allan Jabri
Pieter Abbeel
Sergey Levine
Chelsea Finn
+ Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning 2018 Wen Sun
J. Andrew Bagnell
Byron Boots
+ Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion 2018 Jacob Buckman
Danijar Hafner
George Tucker
Eugene Brevdo
Honglak Lee
+ PDF Chat Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning 2018 Anusha Nagabandi
Gregory Kahn
Ronald S. Fearing
Sergey Levine
+ A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning 2010 Stéphane Ross
Geoffrey J. Gordon
J. Andrew Bagnell
+ PDF Chat Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system 2018 Kendall Lowrey
Svetoslav Kolev
Jeremy Dao
Aravind Rajeswaran
Emanuel Todorov
+ Asynchronous Methods for Deep Reinforcement Learning 2016 Volodymyr Mnih
Adrià Puigdomènech Badia
Mehdi Mirza
Alex Graves
Tim Harley
Timothy Lillicrap
David Silver
Koray Kavukcuoglu
+ PDF Chat Learning dexterous in-hand manipulation 2019 OpenAI Marcin Andrychowicz
Bowen Baker
Maciek Chociej
Rafał Józefowicz
Bob McGrew
Jakub Pachocki
Arthur J Petron
Matthias Plappert
Glenn Powell
Alex Ray
+ PDF Chat Sim-to-Real Transfer of Robotic Control with Dynamics Randomization 2018 Xue Bin Peng
Marcin Andrychowicz
Wojciech Zaremba
Pieter Abbeel
+ Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models 2015 Bradly C. Stadie
Sergey Levine
Pieter Abbeel