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Cited by 216

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

EPAM-like models of recognition and learning

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FEIGENBAUM, E, SIMON, H·1984·Cognitive Science

Abstract

A description is provided of EPAM-III, a theory in the form of a computer program for simulating human verbal learning, along with a summary of the empirical evidence for its validity. Criticisms leveled against the theory in a recent paper by Barsalou and Bower are shown to derive largely from their misconception that EPAM-III employed a binary, rather than n-ary branching discrimination net. It is shown that Barsalou and Bower also failed to understand how the recursive structure of EPAM-III eliminates the need to duplicate test nodes that are used to recognize subobjects, and how the possibility of redundant recognition paths controls the sensitivity of EPAM to noticing order. EPAM is also compared briefly with other theories of human discrimination and discrimination learning, including PANDEMONIUM-like systems and dataflow nets.

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Metadata

Authors
FEIGENBAUM, E., & SIMON, H.
Venue
Cognitive Science
Publisher
Wiley
Published
1984-12
Volume
8
Issue
4
Pages
305-336
ISSN
0364-0213 (ISSN-L)
OpenAlex
W2070618299
Cited by
216
References
6
FWCI
2.49
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: EPAM-like models of recognition and learning. https://app.cochat.ai/papers/10.1016/s0364-0213(84)80005-1
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FEIGENBAUM, E., & SIMON, H. (1984). EPAM-like models of recognition and learning. Cognitive Science. https://doi.org/10.1016/s0364-0213(84)80005-1

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