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Sampling-based Model Predictive Control (MPC) has been a practical and effective approach in many domains, notably model-based reinforcement learning, thanks to its flexibility and parallelizability.
A second-order gradient method for determining optimal trajectories of non-linear discrete-time systems
David Mayne · 1966
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Using the Cross-Entropy Method to Guide/Govern Mobile Agent’s Path Finding in Networks
Bjarne E. Helvik and Otto Wittner · 2001
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Simulated annealing overview
Franco Busetti · 2003
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Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES)
Nikolaus Hansen, Sibylle D. Müller, and Petros Koumoutsakos · 2003
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The Cross Entropy Method for Fast Policy Search
Shie Mannor, Reuven Rubinstein, and Yohai Gat · 2003
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Iterative linear quadratic regulator design for nonlinear biological movement systems
Weiwei Li and Emanuel Todorov · 2004
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Basis Function Adaptation in Temporal Difference Reinforcement Learning
Ishai Menache, Shie Mannor, and Nahum Shimkin · 2005
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An efficient sequential linear quadratic algorithm for solving nonlinear optimal control problems
A. Sideris and J.E. Bobrow · 2005
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Learning tetris using the noisy cross-entropy method, 2006
István Szita and András Lörincz · 2006
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Cross-Entropy Randomized Motion Planning
Hugh Durrant-Whyte, Nicholas Roy, and Pieter Abbeel · 2012
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Chapter 3 - The Cross-Entropy Method for Optimization
Zdravko I. Botev, Dirk P. Kroese, Reuven Y. Rubinstein, and Pierre L’Ecuyer · 2013
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Control-limited differential dynamic programming
Yuval Tassa, Nicolas Mansard, and Emo Todorov · 2014
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Model Predictive Control in Industry: Challenges and Opportunities
Michael G. Forbes, Rohit S. Patwardhan, Hamza Hamadah, and R. Bhushan Gopaluni · 2015
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Robust and stochastic model predictive control: Are we going in the right direction?
David Mayne · 2016
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Aggressive driving with model predictive path integral control
Grady Williams, Paul Drews, Brian Goldfain, James M. Rehg, and Evangelos A. Theodorou · 2016
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Crazyflie 2.0 quadrotor as a platform for research and education in robotics and control engineering
Wojciech Giernacki, Mateusz Skwierczyński, Wojciech Witwicki, Paweł Wroński, and Piotr Kozierski · 2017
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Crazyswarm: A large nano-quadcopter swarm
James A. Preiss, Wolfgang Honig, Gaurav S. Sukhatme, and Nora Ayanian · 2017
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Information theoretic MPC for model-based reinforcement learning
Grady Williams, Nolan Wagener, Brian Goldfain, Paul Drews, James M. Rehg, Byron Boots, and Evangelos A. Theodorou · 2017
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Trajectory Optimization With Implicit Hard Contacts
Jan Carius, René Ranftl, Vladlen Koltun, and Marco Hutter · 2018
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Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models, November 2018
Kurtland Chua, Roberto Calandra, Rowan McAllister, and Sergey Levine · 2018
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Vision-Based High Speed Driving with a Deep Dynamic Observer, December 2018
Paul Drews, Grady Williams, Brian Goldfain, Evangelos A. Theodorou, and James M. Rehg · 2018
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Model-Based Offline Planning, March 2021
Arthur Argenson and Gabriel Dulac-Arnold · 2021
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Robust Model Predictive Path Integral Control: Analysis and Performance Guarantees
Manan S. Gandhi, Bogdan Vlahov, Jason Gibson, Grady Williams, and Evangelos A. Theodorou · 2021
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When to Trust Your Model: Model-Based Policy Optimization, November 2021
Michael Janner, Justin Fu, Marvin Zhang, and Sergey Levine · 2021
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Perturbation-based regret analysis of predictive control in linear time varying systems
Yiheng Lin, Yang Hu, Guanya Shi, Haoyuan Sun, Guannan Qu, and Adam Wierman · 2021
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Temporal Predictive Coding For Model-Based Planning In Latent Space, June 2021
Tung Nguyen, Rui Shu, Tuan Pham, Hung Bui, and Stefano Ermon · 2021
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Frederik Ebert, Chelsea Finn, Sudeep Dasari, Annie Xie, Alex Lee, and Sergey Levine · 2018
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Learning Latent Dynamics for Planning from Pixels, June 2019
Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, and James Davidson · 2019
Cited alongside, same era.
Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control, January 2019
Kendall Lowrey, Aravind Rajeswaran, Sham Kakade, Emanuel Todorov, and Igor Mordatch · 2019
Cited alongside, same era.
Neural lander: Stable drone landing control using learned dynamics
Guanya Shi, Xichen Shi, Michael O’Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, and Soon-Jo Chung · 2019
Cited alongside, same era.
An Online Learning Approach to Model Predictive Control
Nolan Wagener, Ching-an Cheng, Jacob Sacks, and Byron Boots · 2019
Cited alongside, same era.
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning, June 2019
Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew J. Johnson, and Sergey Levine · 2019
Cited alongside, same era.
Information Theoretic Model Predictive Q-Learning, May 2020
Mohak Bhardwaj, Ankur Handa, Dieter Fox, and Byron Boots · 2020
Cited alongside, same era.
Guanya Shi, Wolfgang Hönig, Xichen Shi, Yisong Yue, and Soon-Jo Chung · 2021
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Variational Inference MPC using Tsallis Divergence, April 2021
Ziyi Wang, Oswin So, Jason Gibson, Bogdan Vlahov, Manan S. Gandhi, Guan-Horng Liu, and Evangelos A. Theodorou · 2021
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Constrained Covariance Steering Based Tube-MPPI, April 2022
Isin M. Balci, Efstathios Bakolas, Bogdan Vlahov, and Evangelos Theodorou · 2022
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Temporal Difference Learning for Model Predictive Control, July 2022
Nicklas Hansen, Xiaolong Wang, and Hao Su · 2022
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Neural-fly enables rapid learning for agile flight in strong winds
Michael O’Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, and Soon-Jo Chung · 2022
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Datt: Deep adaptive trajectory tracking for quadrotor control
Kevin Huang, Rwik Rana, Alexander Spitzer, Guanya Shi, and Byron Boots · 2023
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Reinforcement Learning Environments in JAX, November 2023
Robert Tjarko Lange · 2023
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Regularized Newton Method with Global $O(1/k2̂)$ Convergence, March 2023
Konstantin Mishchenko · 2023
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Deep Model Predictive Optimization, October 2023
Jacob Sacks, Rwik Rana, Kevin Huang, Alex Spitzer, Guanya Shi, and Byron Boots · 2023
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Reaching the limit in autonomous racing: Optimal control versus reinforcement learning
Yunlong Song, Angel Romero, Matthias Müller, Vladlen Koltun, and Davide Scaramuzza · 2023
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