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In many applications, it is desirable to extract only the relevant information from complex input data, which involves making a decision about which input features are relevant.
Infobot: Transfer and exploration via the information bottleneck
Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew Botvinick, Hugo Larochelle, Sergey Levine, and Yoshua Bengio · 1901
Earlier work this paper cites.
Recurrent independent mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, and Bernhard Schölkopf · 1909
Earlier work this paper cites.
Philosophical Transactions of the Royal Society B: Biological Sciences , 308(1135):67–78, 1985
Actions and habits: the development of behavioural autonomy · 1985
Earlier work this paper cites.
The empirical case for two systems of reasoning
Steven A Sloman · 1996
Earlier work this paper cites.
Reinforcement learning: An introduction
Richard S Sutton, Andrew G Barto, et al · 1998
Earlier work this paper cites.
The information bottleneck method
Naftali Tishby, Fernando C. N. Pereira, and William Bialek · 2000
Earlier work this paper cites.
Maps of bounded rationality: Psychology for behavioral economics
Daniel Kahneman · 2003
Earlier work this paper cites.
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Thomas M. Cover and Joy A. Thomas · 2006
Earlier work this paper cites.
Grounding subgoals in information transitions
S. G. van Dijk and D. Polani · 2011
Earlier work this paper cites.
An information-theoretic approach to curiosity-driven reinforcement learning
Susanne Still and Doina Precup · 2012
Earlier work this paper cites.
Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Alex Graves, Greg Wayne, and Ivo Danihelka · 2014
Cited alongside, same era.
Recurrent models of visual attention
Volodymyr Mnih, Nicolas Heess, Alex Graves, et al · 2014
Cited alongside, same era.
Motivation and cognitive control: from behavior to neural mechanism
Matthew Botvinick and Todd Braver · 2015
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Variational information maximisation for intrinsically motivated reinforcement learning
Shakir Mohamed and Danilo Jimenez Rezende · 2015
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Universal value function approximators
Karol Gregor, Danilo Jimenez Rezende, and Daan Wierstra · 2016
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Vime: Variational information maximizing exploration
Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, and Pieter Abbeel · 2016
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Learning multiagent communication with backpropagation
Sainbayar Sukhbaatar, Rob Fergus, et al · 2016
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Emergence of grounded compositional language in multi-agent populations
Igor Mordatch and Pieter Abbeel · 2017
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Imagination-augmented agents for deep reinforcement learning
Sébastien Racanière, Théophane Weber, David Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adria Puigdomenech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, et al · 2017
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Tom Schaul, Daniel Horgan, Karol Gregor, and David Silver · 2015
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End-to-end memory networks
Sainbayar Sukhbaatar, Jason Weston, Rob Fergus, et al · 2015
Cited alongside, same era.
Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio · 2015
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Information dropout: learning optimal representations through noise
Alessandro Achille and Stefano Soatto · 2016
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Deep variational information bottleneck
Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, and Kevin Murphy · 2016
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Learning to communicate with deep multi-agent reinforcement learning
Jakob Foerster, Ioannis Alexandros Assael, Nando de Freitas, and Shimon Whiteson · 2016
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Toward a rational and mechanistic account of mental effort
Amitai Shenhav, Sebastian Musslick, Falk Lieder, Wouter Kool, Thomas L Griffiths, Jonathan D Cohen, and Matthew M Botvinick · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Minimalistic gridworld environment for openai gym
Maxime Chevalier-Boisvert and Lucas Willems · 2018
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Babyai: First steps towards grounded language learning with a human in the loop
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, and Yoshua Bengio · 2018
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Representation learning for grounded spatial reasoning
Michael Janner, Karthik Narasimhan, and Regina Barzilay · 2018
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Sparse attentive backtracking: Temporal credit assignment through reminding
Nan Rosemary Ke, Anirudh Goyal ALIAS PARTH GOYAL, Olexa Bilaniuk, Jonathan Binas, Michael C Mozer, Chris Pal, and Yoshua Bengio · 2018
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