Topics in Cognitive Science 7 (2):217-229 (2015)
Abstract |
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.”
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Keywords | Rational process models Bayesian models of cognition Levels of analysis Algorithmic level Resource‐rational models Computational level |
Categories | (categorize this paper) |
DOI | 10.1111/tops.12142 |
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References found in this work BETA
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Citations of this work BETA
Book: Cognitive Design for Artificial Minds.Antonio Lieto - 2021 - London, UK: Routledge, Taylor & Francis Ltd.
Beyond Automaticity: The Psychological Complexity of Skill.Elisabeth Pacherie & Myrto Mylopoulos - 2020 - Topoi 40 (3):649-662.
Subjective Probability as Sampling Propensity.Thomas Icard - 2016 - Review of Philosophy and Psychology 7 (4):863-903.
How We Know What Not To Think.Jonathan Phillips, Adam Morris & Fiery Cushman - 2019 - Trends in Cognitive Sciences 23 (12):1026-1040.
Rational monism and rational pluralism.Jack Spencer - 2020 - Philosophical Studies 178 (6):1769-1800.
View all 41 citations / Add more citations
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