Oaksford, Mike and Chater, N. and Stenning, K. (1990) Connectionism, classical cognitive science and experimental psychology. AI & Society 4 (1), pp. 73-90. ISSN 0951-5666.
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.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | Connectionism, Classical cognitive science, Experimental psychology, MemoryInference |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Psychological Sciences |
| Depositing User: | Administrator |
| Date Deposited: | 15 Sep 2016 16:32 |
| Last Modified: | 02 Aug 2023 17:26 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/16061 |
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