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Categorial Compositionality: A Category Theory Explanation for the Systematicity of Human Cognition

Overview of attention for article published in PLoS Computational Biology, July 2010
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Title
Categorial Compositionality: A Category Theory Explanation for the Systematicity of Human Cognition
Published in
PLoS Computational Biology, July 2010
DOI 10.1371/journal.pcbi.1000858
Pubmed ID
Authors

Steven Phillips, William H. Wilson

Abstract

Classical and Connectionist theories of cognitive architecture seek to explain systematicity (i.e., the property of human cognition whereby cognitive capacity comes in groups of related behaviours) as a consequence of syntactically and functionally compositional representations, respectively. However, both theories depend on ad hoc assumptions to exclude specific instances of these forms of compositionality (e.g. grammars, networks) that do not account for systematicity. By analogy with the Ptolemaic (i.e. geocentric) theory of planetary motion, although either theory can be made to be consistent with the data, both nonetheless fail to fully explain it. Category theory, a branch of mathematics, provides an alternative explanation based on the formal concept of adjunction, which relates a pair of structure-preserving maps, called functors. A functor generalizes the notion of a map between representational states to include a map between state transformations (or processes). In a formal sense, systematicity is a necessary consequence of a higher-order theory of cognitive architecture, in contrast to the first-order theories derived from Classicism or Connectionism. Category theory offers a re-conceptualization for cognitive science, analogous to the one that Copernicus provided for astronomy, where representational states are no longer the center of the cognitive universe--replaced by the relationships between the maps that transform them.

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Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 5%
Japan 2 2%
United Kingdom 2 2%
Korea, Republic of 1 <1%
Australia 1 <1%
Switzerland 1 <1%
Finland 1 <1%
New Zealand 1 <1%
France 1 <1%
Other 4 4%
Unknown 84 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 22%
Researcher 19 18%
Student > Master 11 11%
Student > Bachelor 10 10%
Professor > Associate Professor 9 9%
Other 24 23%
Unknown 7 7%
Readers by discipline Count As %
Computer Science 23 22%
Psychology 17 17%
Agricultural and Biological Sciences 13 13%
Engineering 7 7%
Mathematics 6 6%
Other 26 25%
Unknown 11 11%