Year: 1995
Type: report
Abstract: The Incremental Analogy Machine (IAM) predicts that the\norder in which parts of an analogy are processed can affect\nthe ease of analogical mapping. In this paper, the\npredictions of this model are tested in two experiments.\nPrevious work has shown that such order effects can be\nfound in attribute-mapping problems. In the first\nexperiment, it is shown that these effects generalise to\nrelational-mapping problems, when subjects' error\nperformance (incorrect mappings) is considered. It is also\nfound that relational-mapping problems are significantly\nharder than attribute-mapping problems. In the second\nexperiment, it is shown using relational-mapping\nproblems, that order effects can be demonstrated for\ndoubles (two sentences about two indiviudals) in these\nproblems. Throughout the paper it is shown that these\nresults are best approximated by IAM's measure of the\ncomplexity of global mappings (the remaps-complexity\nmeasure), and not as has been found previously, by a\nmeasure using frequency of remaps (the re-maps measure).\nThe empirical and theoretical significance of these results\nare discussed.
Author: Mark T. Keane
Institution: Trinity College Dublin
Language: English
Subfield: Linguistics and Language
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
Funder: Trinity College Dublin
OpenAlex ID: W1597433150