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Learning policies for complex tasks that require multiple different skills is a major challenge in reinforcement learning (RL).
Statistical inference for probabilistic functions of finite state markov chains
Leonard E. Baum and Ted Petrie · 1966
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Between mdps anad semi-mdps: A framework fro temporal abstraction in reinforcement learning
Richard S. Sutton, Doina Precup, and Satinder Singh · 1999
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Unsupervised learning of event and-or grammar and semantics from video
Zhangzhang Si, Mingtao Pei, Benjamin Yao, and Song-Chun Zhu · 2011
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Deep learning of representations for unsupervised and transfer learning
Yoshua Bengio · 2012
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Lecture 6.5—rmsprop: Divide the gradient by a running average of its recent magnitude
Tijmen Tieleman and Geoffrey Hinto · 2012
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Parsing videos of actions with segmental grammars
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The option-critic architecture
Pierre-Luc Bacon and Doina Precup · 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, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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Language understanding for text-based games using deep reinforcement learning
Karthik Narasimhan, Tejas Kulkarni, and Regina Barzilay · 2015
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The malmo platform for artificial intelligence experimentation
Matthew Johnson, Katja Hofmann, Tim Hutton, and David Bignell · 2016
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Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Tocze, and Wojciech Jaśkowski · 2016
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Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation
Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, , and Josh Tenenbaum · 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
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Actor-mimic: Deep multitask and transfer reinforcement learning
Emilio Parisotto, Jimmy Lei Ba, and Ruslan Salakhutdinov · 2016
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Modular multitask reinforcement learning with policy sketches
Jacob Andreas, Dan Klein, and Sergey Levine · 2017
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Gated-attention architectures for task-oriented language grounding
Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, and Ruslan Salakhutdinov · 2017
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Grounded language learning in a simulated 3d world
Karl Moritz Hermann, Felix Hill, Simon Green, Fumin Wang, Ryan Faulkner, Hubert Soyer, David Szepesvari, Wojtek Czarnecki, Max Jaderberg, Denis Teplyashin, Marcus Wainwright, Chris Apps, Demis Hassabis, and Phil Blunsom · 2017
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Learning to navigate in complex environments
Piotr Mirowski, Razvan Pascanu, Fabio Viola, Hubert Soyer, Andy Ballard, Andrea Banino, Misha Denil, Ross Goroshin, Laurent Sifre, Koray Kavukcuoglu, Dharshan Kumaran, and Raia Hadsell · 2017
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Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George Van Den Driessche, Thore Graepel, and Demis Hassabis · 2017
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Policy distillation
Andrei A Rusu, Sergio Gomez Colmenarejo, Caglar Gulcehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, and Raia Hadsell · 2016
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Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, and Julian Schrittwieser et al · 2016
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Strategic attentive writer for learning macro-actions
Alexander (Sasha) Vezhnevets, Volodymyr Mnih, John Agapiou, Simon Osindero, Alex Graves, Orial Vinyals, and Koray Kavukcuoglu · 2016
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End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel
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Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, , and Deirdre Quillen
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Sample-efficient actor-critic reinforcement learning with supervised data for dialogue management
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Sample efficient actor-critic with experience replay
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