, Volume 4, Issue 1, pp 73–90 | Cite as

Connectionism, classical cognitive science and experimental psychology

  • Mike Oaksford
  • Nick Chater
  • Keith Stenning


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.


Connectionism Classical cognitive science Experimental psychology Memory Inference 


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Copyright information

© Springer-Verlag London Limited 1990

Authors and Affiliations

  • Mike Oaksford
    • 1
  • Nick Chater
    • 1
  • Keith Stenning
    • 1
  1. 1.Centre for Cognitive ScienceUniversity of EdinburghUK

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