Connectionism, classical cognitive science and experimental psychology

AI and Society 4 (1):73-90 (1990)
  Copy   BIBTEX

Abstract

Classical symbolic computational models of cognition are at variance with the empirical findings in the cognitive psychology of memory and inference. Standard symbolic computers are well suited to remembering arbitrary lists of symbols and performing logical inferences. In contrast, human performance on such tasks is extremely limited. Standard models donot easily capture content addressable memory or context sensitive defeasible inference, which are natural and effortless for people. We argue that Connectionism provides a more natural framework in which to model this behaviour. In addition to capturing the gross human performance profile, Connectionist systems seem well suited to accounting for the systematic patterns of errors observed in the human data. We take these arguments to counter Fodor and Pylyshyn's (1988) recent claim that Connectionism is, in principle, irrelevant to psychology

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 90,221

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Analytics

Added to PP
2009-01-28

Downloads
89 (#174,844)

6 months
4 (#315,466)

Historical graph of downloads
How can I increase my downloads?

Author Profiles

References found in this work

The Language of Thought.Jerry A. Fodor - 1975 - Harvard University Press.
The Structure of Scientific Revolutions.Thomas S. Kuhn - 1962 - Chicago, IL: University of Chicago Press. Edited by Ian Hacking.
Criticism and the growth of knowledge.Imre Lakatos & Alan Musgrave (eds.) - 1970 - Cambridge [Eng.]: Cambridge University Press.

View all 38 references / Add more references