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Thomas L. Griffiths

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Meta-Learning of Compositional Task Distributions in Humans and Machines

Oct 05, 2020
Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths

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Learning Rewards from Linguistic Feedback

Sep 30, 2020
Theodore R. Sumers, Mark K. Ho, Robert D. Hawkins, Karthik Narasimhan, Thomas L. Griffiths

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Understanding Human Intelligence through Human Limitations

Sep 29, 2020
Thomas L. Griffiths

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Resource-rational Task Decomposition to Minimize Planning Costs

Jul 27, 2020
Carlos G. Correa, Mark K. Ho, Fred Callaway, Thomas L. Griffiths

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End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior

Jul 17, 2020
Pulkit Singh, Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths

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Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions

Jul 05, 2020
Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Thomas L. Griffiths, Sergey Levine

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Universal linguistic inductive biases via meta-learning

Jun 29, 2020
R. Thomas McCoy, Erin Grant, Paul Smolensky, Thomas L. Griffiths, Tal Linzen

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Analogy as Nonparametric Bayesian Inference over Relational Systems

Jun 07, 2020
Ruairidh M. Battleday, Thomas L. Griffiths

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Extracting low-dimensional psychological representations from convolutional neural networks

May 29, 2020
Aditi Jha, Joshua Peterson, Thomas L. Griffiths

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The Efficiency of Human Cognition Reflects Planned Information Processing

Feb 13, 2020
Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths

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