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{{Short description|Approach in cognitive science that hopes to explain mental phenomena using artificial neural networks}}
{{more footnotes|date=April 2014}}
'''Connectionism''' is an approach in the fields of [[cognitive science]] that hopes to explain [[mind|mental]] phenomena using [[artificial neural networks]] (ANN).<ref name=":0">{{cite book|url=https://plato.stanford.edu/archives/fall2018/entries/connectionism/|title=The Stanford Encyclopedia of Philosophy|first=James|last=Garson|editor-first=Edward N.|editor-last=Zalta|date=27 November 2018|publisher=Metaphysics Research Lab, Stanford University|via=Stanford Encyclopedia of Philosophy}}</ref> Connectionism presents a cognitive theory based on simultaneously occurring, distributed signal activity via connections that can be represented numerically, where learning occurs by modifying connection strengths based on experience.<ref name=":1">{{Cite journal|last=Smolensky|first=Paul|date=1999|title=Grammar-based Connectionist Approaches to Language|url=http://csjarchive.cogsci.rpi.edu/1999v23/i04/p0589p0613/MAIN.PDF|journal=Cognitive Science|volume=23|issue=4|pages=589–613|doi=10.1207/s15516709cog2304_9|doi-access=free}}</ref>
Some advantages of the connectionist approach include its applicability to a broad array of functions, structural approximation to biological neurons, low requirements for innate structure, and capacity for [[graceful degradation]].<ref name=":2">{{Cite book|title=The Algebraic Mind: Integrating Connectionism and Cognitive Science (Learning, Development, and Conceptual Change)|url=https://archive.org/details/algebraicmindint00marc_403|url-access=limited|last=Marcus|first=Gary F.|publisher=MIT Press|year=2001|isbn=978-0262632683|location=Cambridge, Massachusetts|pages=[https://archive.org/details/algebraicmindint00marc_403/page/n43 27]–28}}</ref> Some disadvantages include the difficulty in deciphering how ANNs process information, or account for the compositionality of mental representations, and a resultant difficulty explaining phenomena at a higher level.<ref name=":1" />
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