Beyond single-level accounts: The role of cognitive architectures in cognitive scientific explanation

Richard P. Cooper, David Peebles

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

We consider approaches to explanation within the cognitive sciences that begin with Marr's computational level (e.g., purely Bayesian accounts of cognitive phenomena) or Marr's implementational level (e.g., reductionist accounts of cognitive phenomena based only on neural-level evidence) and argue that each is subject to fundamental limitations which impair their ability to provide adequate explanations of cognitive phenomena. For this reason, it is argued, explanation cannot proceed at either level without tight coupling to the algorithmic and representation level. Even at this level, however, we argue that additional constraints relating to the decomposition of the cognitive system into a set of interacting subfunctions (i.e., a cognitive architecture) are required. Integrated cognitive architectures that permit abstract specification of the functions of components and that make contact with the neural level provide a powerful bridge for linking the algorithmic and representational level to both the computational level and the implementational level.

Original languageEnglish
Pages (from-to)243-258
Number of pages16
JournalTopics in Cognitive Science
Volume7
Issue number2
DOIs
Publication statusPublished - 1 Apr 2015

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