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Computational-representational understanding of mind

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This is an old revision of this page, as edited by Calrad (talk | contribs) at 18:49, 30 April 2016 (Paul Thagard's opinion of CRUM is not definitive; quote needed citation to his argument and ref to other researchers.). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Computational representational understanding of mind (abbreviated CRUM) is a hypothesis in cognitive science which proposes that thinking is performed by computations operating on representations. This hypothesis assumes that the mind has mental representations analogous to data structures and computational procedures analogous to algorithms, such that computer programs using algorithms applied to data structures can model the mind and its processes.

CRUM takes into consideration several theoretical approaches of understanding human cognition, including logic, rule, concept, analogy, image, and connection based systems. These serve as the representation aspects of CRUM theory which are then acted upon to simulate certain aspects of human cognition, such as the use of rule-based systems in neuroeconomics.

There is much disagreement on this hypothesis, but CRUM has high regard among some researchers [citation needed]. Philosopher Paul Thagard called it "the most theoretically and experimentally successful approach to mind ever developed" [citation needed].

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