Fetching the paper…
Reading the bibliography…
Learning to drive faithfully in highly stochastic urban settings remains an open problem.
Temporal credit assignment in reinforcement learning
Richard Stuart Sutton · 1984
Earlier work this paper cites.
Distributed hierarchical processing in the primate cerebral cortex
Daniel J Felleman and DC Essen Van · 1991
Earlier work this paper cites.
Introduction: The challenge of reinforcement learning
Richard S Sutton · 1992
Earlier work this paper cites.
Origins and early development of perception, action, and representation
Bennett I. Bertenthal · 1996
Earlier work this paper cites.
Reinforcement learning: A survey
Leslie Pack Kaelbling, Michael L Littman, and Andrew W Moore · 1996
Earlier work this paper cites.
Robot learning from demonstration
Christopher G Atkeson and Stefan Schaal · 1997
Earlier work this paper cites.
Learning from demonstration
Stefan Schaal · 1997
Earlier work this paper cites.
Learning by imitation: A hierarchical approach
Richard W Byrne and Anne E Russon · 1998
Earlier work this paper cites.
Multitask learning
Rich Caruana · 1998
Earlier work this paper cites.
Reinforcement learning: An introduction , volume 1
Richard S Sutton and Andrew G Barto · 1998
Earlier work this paper cites.
Principles of neural science , volume 4
Eric R Kandel, James H Schwartz, Thomas M Jessell, Steven A Siegelbaum, A James Hudspeth, et al · 2000
Earlier work this paper cites.
Sensory-motor primitives as a basis for imitation: Linking perception to action and biology to robotics
Maja J. Mataric · 2000
Earlier work this paper cites.
From motor babbling to hierarchical learning by imitation: a robot developmental pathway
Yiannis Demiris and Anthony Dearden · 2005
Earlier work this paper cites.
Motor primitives in vertebrates and invertebrates
Tamar Flash and Binyamin Hochner · 2005
Earlier work this paper cites.
Imitation of hierarchical action structure by young children
Andrew Whiten, Emma Flynn, Katy Brown, and Tanya Lee · 2006
Earlier work this paper cites.
A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston · 2008
Earlier work this paper cites.
Dual-processing accounts of reasoning, judgment, and social cognition
Jonathan St BT Evans · 2008
Earlier work this paper cites.
A survey of robot learning from demonstration
Brenna D Argall, Sonia Chernova, Manuela Veloso, and Brett Browning · 2009
Earlier work this paper cites.
Learning to search: Functional gradient techniques for imitation learning
Nathan D Ratliff, David Silver, and J Andrew Bagnell · 2009
Earlier work this paper cites.
Evidence for model-based action planning in a sequential finger movement task
Alan Fermin, Takehiko Yoshida, Makoto Ito, Junichiro Yoshimoto, and Kenji Doya · 2010
Cited alongside, same era.
States versus rewards: dissociable neural prediction error signals underlying model-based and model-free reinforcement learning
Jan Gläscher, Nathaniel Daw, Peter Dayan, and John P O’Doherty · 2010
Cited alongside, same era.
A neural basis for motor primitives in the spinal cord
Corey B Hart and Simon F Giszter · 2010
Cited alongside, same era.
No-regret reductions for imitation learning and structured prediction
Stéphane Ross, Geoffrey J. Gordon, and J. Andrew Bagnell · 2010
Cited alongside, same era.
Separate encoding of model-based and model-free valuations in the human brain
Ulrik R Beierholm, Cedric Anen, Steven Quartz, and Peter Bossaerts · 2011
Cited alongside, same era.
"why should I trust you?": Explaining the predictions of any classifier
Marco Túlio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
Later among the works it cites.
Deep-learning in mobile robotics - from perception to control systems: A survey on why and why not
Lei Tai and Ming Liu · 2016
Later among the works it cites.
A deep-network solution towards model-less obstacle avoidance
Lei Tai, Shaohua Li, and Ming Liu · 2016
Later among the works it cites.
End-to-end learning of driving models from large-scale video datasets
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell · 2016
Later among the works it cites.
Augmenting supervised neural networks with unsupervised objectives for large-scale image classification
Yuting Zhang, Kibok Lee, and Honglak Lee · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Cited alongside, same era.
A convex formulation for learning task relationships in multi-task learning
Yu Zhang and Dit-Yan Yeung · 2012
Cited alongside, same era.
New types of deep neural network learning for speech recognition and related applications: An overview
Li Deng, Geoffrey Hinton, and Brian Kingsbury · 2013
Cited alongside, same era.
Guided policy search
Sergey Levine and Vladlen Koltun · 2013
Cited alongside, same era.
Multi-task learning in deep neural networks for improved phoneme recognition
Michael L Seltzer and Jasha Droppo · 2013
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
Cited alongside, same era.
Deepdriving: Learning affordance for direct perception in autonomous driving
Chenyi Chen, Ari Seff, Alain L. Kornhauser, and Jianxiong Xiao · 2015
Cited alongside, same era.
Explaining how a deep neural network trained with end-to-end learning steers a car
Mariusz Bojarski, Philip Yeres, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Lawrence Jackel, and Urs Muller · 2017
Later among the works it cites.
End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias Müller, Alexey Dosovitskiy, Antonio López, and Vladlen Koltun · 2017
Later among the works it cites.
Carla: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio López, and Vladlen Koltun · 2017
Later among the works it cites.
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, and Wojciech Zaremba · 2017
Later among the works it cites.
One-shot visual imitation learning via meta-learning
Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, and Sergey Levine · 2017
Later among the works it cites.
Fast recurrent fully convolutional networks for direct perception in autonomous driving
Yiqi Hou, Sascha Hornauer, and Karl Zipser · 2017
Later among the works it cites.
Iterative noise injection for scalable imitation learning
Michael Laskey, Jonathan Lee, Wesley Yu-Shu Hsieh, Richard Liaw, Jeffrey Mahler, Roy Fox, and Ken Goldberg · 2017
Later among the works it cites.
An overview of multi-task learning in deep neural networks
Sebastian Ruder · 2017
Later among the works it cites.
Wojciech Samek, Thomas Wiegand, and Klaus-Robert Müller · 2017
Later among the works it cites.
Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi · 2017
Later among the works it cites.
Hierarchical imitation and reinforcement learning
Hoang M. Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, and Hal Daumé III · 2018
Closest in time.
Deep learning: A critical appraisal
Gary Marcus · 2018
Closest in time.
TACO: learning task decomposition via temporal alignment for control
Kyriacos Shiarlis, Markus Wulfmeier, Sasha Salter, Shimon Whiteson, and Ingmar Posner · 2018
Closest in time.
One-shot imitation from observing humans via domain-adaptive meta-learning
Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, and Sergey Levine · 2018
Closest in time.