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Recent work has explored the problem of autonomous navigation by imitating a teacher and learning an end-to-end policy, which directly predicts controls from raw images.
Introduction to reinforcement learning , volume 135
Richard S Sutton and Andrew G Barto · 1998
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Policy invariance under reward transformations: Theory and application to reward shaping
Andrew Y Ng, Daishi Harada, and Stuart Russell · 1999
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Natural actor-critic
Jan Peters, Sethu Vijayakumar, and Stefan Schaal · 2005
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Efficient reductions for imitation learning
Stephane Ross and Drew Bagnell · 2010
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No-regret reductions for imitation learning and structured prediction
Stephane Ross, Geoffrey J. Gordon, and J. Andrew Bagnell · 2010
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Integrating reinforcement learning with human demonstrations of varying ability
Matthew E. Taylor, Halit Bener Suay, and Sonia Chernova · 2011
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Guided policy search
Sergey Levine and Vladlen Koltun · 2013
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Online Evolution of Deep Convolutional Network for Vision-Based Reinforcement Learning , pages 260–269
Jan Koutník, Jürgen Schmidhuber, and Faustino Gomez · 2014
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Reinforcement and imitation learning via interactive no-regret learning
Stephane Ross and J Andrew Bagnell · 2014
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Learning to search better than your teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daumé III, and John Langford · 2015
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Deepdriving: Learning affordance for direct perception in autonomous driving
Chenyi Chen, Ari Seff, Alain Kornhauser, and Jianxiong Xiao · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Trust region policy optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz · 2015
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End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, and Karol Zieba · 2016
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Virtual worlds as proxy for multi-object tracking analysis
Adrien Gaidon, Qiao Wang, Yohann Cabon, and Eleonora Vig · 2016
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Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
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Learning physical intuition of block towers by example
Adam Lerer, Sam Gross, and Rob Fergus · 2016
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Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2016
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Playing for data: Ground truth from computer games
Stephan R. Richter, Vibhav Vineet, Stefan Roth, and Vladlen Koltun · 2016
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The SYNTHIA Dataset: A large collection of synthetic images for semantic segmentation of urban scenes
German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, and Antonio Lopez · 2016
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End-to-end deep reinforcement learning for lane keeping assist
Ahmad El Sallab, Mohammed Abdou, Etienne Perot, and Senthil Yogamani · 2016
Reinforcement learning from imperfect demonstrations
Yang Gao, Huazhe Xu, Ji Lin, Fisher Yu, Sergey Levine, and Trevor Darrell · 2018
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Reinforcement learning with multiple experts: A bayesian model combination approach
Michael Gimelfarb, Scott Sanner, and Chi-Guhn Lee · 2018
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Navigating occluded intersections with autonomous vehicles using deep reinforcement learning
David Isele, Reza Rahimi, Akansel Cosgun, Kaushik Subramanian, and Kikuo Fujimura · 2018
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Deep drone racing: Learning agile flight in dynamic environments
Elia Kaufmann, Antonio Loquercio, Rene Ranftl, Alexey Dosovitskiy, Vladlen Koltun, and Davide Scaramuzza · 2018
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Learning good policies from suboptimal demonstrations
Yuxiang Li, Ian Kash, and Katja Hofmann · 2018
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CIRL: controllable imitative reinforcement learning for vision-based self-driving
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End-to-end learning of driving models from large-scale video datasets
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell · 2016
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Query-efficient imitation learning for end-to-end autonomous driving
Jiakai Zhang and Kyunghyun Cho · 2016
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Deep learning quadcopter control via risk-aware active learning
Olov Andersson, Mariusz Wzorek, and Patrick Doherty · 2017
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Learning to act by predicting the future
Alexey Dosovitskiy and Vladlen Koltun · 2017
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CARLA: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
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Deep reinforcement learning framework for autonomous driving
Ahmad EL Sallab, Mohammed Abdou, Etienne Perot, and Senthil Yogamani · 2017
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Airsim: High-fidelity visual and physical simulation for autonomous vehicles
Shital Shah, Debadeepta Dey, Chris Lovett, and Ashish Kapoor · 2017
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Xiaodan Liang, Tairui Wang, Luona Yang, and Eric Xing · 2018
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Teaching UAVs to Race: End-to-End Regression of Agile Controls in Simulation
M. Müller, V. Casser, N. Smith, D. L. Michels, and B. Ghanem · 2018
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Sim4cv: A photo-realistic simulator for computer vision applications
Matthias Müller, Vincent Casser, Jean Lahoud, Neil Smith, and Bernard Ghanem · 2018
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Driving policy transfer via modularity and abstraction
Matthias Müller, Alexey Dosovitskiy, Bernard Ghanem, and Vladlen Koltun · 2018
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Agile autonomous driving using end-to-end deep imitation learning
Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos Theodorou, and Byron Boots · 2018
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Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov, and Sergey Levine · 2018
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Conditional affordance learning for driving in urban environments
Axel Sauer, Nikolay Savinov, and Andreas Geiger · 2018
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A real-time game theoretic planner for autonomous two-player drone racing
Riccardo Spica, Davide Falanga, Eric Cristofalo, Eduardo Montijano, Davide Scaramuzza, and Mac Schwager · 2018
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Behavioral cloning from observation
Faraz Torabi, Garrett Warnell, and Peter Stone · 2018
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Reinforcement and imitation learning for diverse visuomotor skills
Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, and Nicolas Heess · 2018
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Learning a controller fusion network by online trajectory filtering for vision-based uav racing
Matthias Müller, Guohao Li, Vincent Casser, Neil Smith, Dominik L. Michels, and Bernard Ghanem · 2019
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