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  1. Building Machines That Learn and Think Like People.Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum & Samuel J. Gershman - 2017 - Behavioral and Brain Sciences 40.
    Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking (...)
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  • Computational Models of Emotion Inference in Theory of Mind: A Review and Roadmap.Desmond C. Ong, Jamil Zaki & Noah D. Goodman - 2019 - Topics in Cognitive Science 11 (2):338-357.
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  • A Computational Framework for Understanding the Roles of Simplicity and Rational Support in People's Behavior Explanations.Alan Jern, Austin Derrow-Pinion & A. J. Piergiovanni - 2021 - Cognition 210:104606.
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  • People Learn Other People’s Preferences Through Inverse Decision-Making.Alan Jern, Christopher G. Lucas & Charles Kemp - 2017 - Cognition 168:46-64.
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