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Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources

Published online by Cambridge University Press:  04 February 2019

Falk Lieder Open the ORCID record for Falk Lieder [Opens in a new window]  and
Thomas L. Griffiths
Falk Lieder
Affiliation:
Max Planck Institute for Intelligent Systems, Tübingen72076, Germany. [email protected]://re.is.mpg.de
Thomas L. Griffiths
Affiliation:
Departments of Psychology and Computer Science, Princeton University, Princeton, New Jersey08544, [email protected]://psych.princeton.edu/person/tom-griffiths
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Abstract

Modeling human cognition is challenging because there are infinitely many mechanisms that can generate any given observation. Some researchers address this by constraining the hypothesis space through assumptions about what the human mind can and cannot do, while others constrain it through principles of rationality and adaptation. Recent work in economics, psychology, neuroscience, and linguistics has begun to integrate both approaches by augmenting rational models with cognitive constraints, incorporating rational principles into cognitive architectures, and applying optimality principles to understanding neural representations. We identify the rational use of limited resources as a unifying principle underlying these diverse approaches, expressing it in a new cognitive modeling paradigm called resource-rational analysis. The integration of rational principles with realistic cognitive constraints makes resource-rational analysis a promising framework for reverse-engineering cognitive mechanisms and representations. It has already shed new light on the debate about human rationality and can be leveraged to revisit classic questions of cognitive psychology within a principled computational framework. We demonstrate that resource-rational models can reconcile the mind's most impressive cognitive skills with people's ostensive irrationality. Resource-rational analysis also provides a new way to connect psychological theory more deeply with artificial intelligence, economics, neuroscience, and linguistics.

Keywords

bounded rationalitycognitive biasescognitive mechanismscognitive modelingrepresentationsresource rationality
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 43 , 2020 , e1
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Copyright © Cambridge University Press 2019

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