The DOI matches its Crossref record; 42 of the 44 references it cites were found in a registry or an index.
Simplicity: a unifying principle in cognitive science?
Abstract
Much of perception, learning and high-level cognition involves finding patterns in data. But there are always infinitely many patterns compatible with any finite amount of data. How does the cognitive system choose 'sensible' patterns? A long tradition in epistemology, philosophy of science, and mathematical and computational theories of learning argues that patterns 'should' be chosen according to how simply they explain the data. This article reviews research exploring the idea that simplicity drives a wide range of cognitive processes. We outline mathematical theory, computational results and empirical data that underpin this viewpoint.
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Cites
Lecture Notes in Artificial Intelligence
Brézillon, P., & Bouquet, P. (1999) · Cited by 7,436
An Introduction to Kolmogorov Complexity and Its Applications
Li, M., & Vitanyi, P. M. B. (2019) · Texts in computer science · doi:10.1007/978-3-030-11298-1 · Cited by 3,769
Sparse coding with an overcomplete basis set: A strategy employed by V1?
Olshausen, B. A., & Field, D. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00169-7 · Cited by 3,642
Some informational aspects of visual perception.
Attneave, F. (1954) · Psychological Review · doi:10.1037/h0054663 · Cited by 2,938
(1961) · Information and Control · doi:10.1016/s0019-9958(61)80064-8 · Cited by 2,904
Toward a Universal Law of Generalization for Psychological Science
Shepard, R. N. (1987) · Science · doi:10.1126/science.3629243 · Cited by 2,416
The Processing of Information and Structure
Royer, F. L., & Garner, W. R. (1974) · The American Journal of Psychology · doi:10.2307/1421985 · Cited by 2,130
An Introduction to Kolmogorov Complexity and Its Applications
Li, M., & Vitanyi, P. M. B. (1997) · Springer eBooks · doi:10.1007/978-1-4757-2606-0 · Cited by 1,792
Perception as Bayesian Inference
(1996) · doi:10.1017/cbo9780511984037 · Cited by 1,425
Miller, G. A. (2013) · David Fulton Publishers eBooks · doi:10.4324/9780203449097-13 · Cited by 1,365
Research works printed but not linked: 2
- Rissanen, J. (1989) Stochastic complexity and statistical inquiry. World Scientific Series in Computer Science (Vol 15), World Scientific.
- Chater, 2002, Generalized law of universal generalization, J. Math. Psychol.
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Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012) · Psychological Science in the Public Interest · doi:10.1177/1529100612451018 · Cited by 2,920
Keil, F. C. (2006) · Annual Review of Psychology · doi:10.1146/annurev.psych.57.102904.190100 · Cited by 1,350
The Effort Paradox: Effort Is Both Costly and Valued
Inzlicht, M., Shenhav, A., & Olivola, C. Y. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.01.007 · Cited by 977
Capturing causal complexity: Heuristics for configurational theorizing
Furnari, S., Crilly, D., Misangyi, V. F., Greckhamer, T., Fiss, P. C., & Aguilera, R. V. (2021) · Academy of Management Review · doi:10.5465/amr.2019.0298 · Cited by 861
Unsupervised Learning of the Morphology of a Natural Language
Goldsmith, J. (2001) · Computational Linguistics · doi:10.1162/089120101750300490 · Cited by 790
Metadata
- Authors
- Chater, N., & Vitányi, P.
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 2003-01
- Volume
- 7
- Issue
- 1
- Pages
- 19-22
- ISSN
- 1364-6613 (ISSN-L)
- OpenAlex
- W2093777421
- Cited by
- 494
- References
- 44
- Citations by year
- 2026: 11 · 2025: 32 · 2024: 22 · 2023: 33 · 2022: 56 · 2021: 42 · 2020: 29 · 2019: 30 · 2018: 24 · 2017: 24 · 2016: 22 · 2015: 20 · 2014: 15 · 2013: 17 · 2012: 19
- FWCI
- 1.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Trends in Cognitive Sciences (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Cognitive Science and Education Research
- Keywords
- simplicity, pattern selection, inductive reasoning, epistemology, philosophy of science, perception, generalization
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