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Evidence from machines that learn and think like people

Published online by Cambridge University Press:  10 November 2017

Kenneth D. Forbus  and
Dedre Gentner
Kenneth D. Forbus
Affiliation:
Department of Computer Science, Northwestern University, Evanston, IL 60208. forbus@northwestern.edu http://www.cs.northwestern.edu/~forbus/
Dedre Gentner
Affiliation:
Department of Psychology, Northwestern University, Evanston, IL 60208. gentner@northwestern.edu http://groups.psych.northwestern.edu/gentner/
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Abstract

We agree with Lake et al.'s trenchant analysis of deep learning systems, including that they are highly brittle and that they need vastly more examples than do people. We also agree that human cognition relies heavily on structured relational representations. However, we differ in our analysis of human cognitive processing. We argue that (1) analogical comparison processes are central to human cognition; and (2) intuitive physical knowledge is captured by qualitative representations, rather than quantitative simulations.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 40 , 2017 , e264
Copyright
Copyright © Cambridge University Press 2017 

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