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Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic
Author(s) -
Griffiths Thomas L.,
Lieder Falk,
Goodman Noah D.
Publication year - 2015
Publication title -
topics in cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.191
H-Index - 56
eISSN - 1756-8765
pISSN - 1756-8757
DOI - 10.1111/tops.12142
Subject(s) - computational model , computational resource , computer science , computational complexity theory , popularity , rational analysis , computational thinking , key (lock) , rationality , computational problem , simple (philosophy) , theoretical computer science , asymptotic computational complexity , cognition , resource (disambiguation) , artificial intelligence , management science , data science , algorithm , epistemology , psychology , social psychology , philosophy , computer network , computer security , neuroscience , economics
Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational‐ and algorithmic‐level models. The key idea is to push the notion of rationality, often used in defining computational‐level models, deeper toward the algorithmic level. We offer a simple recipe for reverse‐engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call “resource‐rational analysis.”