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ERIC Number: EJ809710
Record Type: Journal
Publication Date: 2008-Sep
Pages: 12
Abstractor: As Provided
Reference Count: 53
ISSN: ISSN-0278-7393
The Role of Causal Models in Analogical Inference
Lee, Hee Seung; Holyoak, Keith J.
Journal of Experimental Psychology: Learning, Memory, and Cognition, v34 n5 p1111-1122 Sep 2008
Computational models of analogy have assumed that the strength of an inductive inference about the target is based directly on similarity of the analogs and in particular on shared higher order relations. In contrast, work in philosophy of science suggests that analogical inference is also guided by causal models of the source and target. In 3 experiments, the authors explored the possibility that people may use causal models to assess the strength of analogical inferences. Experiments 1-2 showed that reducing analogical overlap by eliminating a shared causal relation (a preventive cause present in the source) from the target increased inductive strength even though it decreased similarity of the analogs. These findings were extended in Experiment 3 to cross-domain analogical inferences based on correspondences between higher order causal relations. Analogical inference appears to be mediated by building and then running a causal model. The implications of the present findings for theories of both analogy and causal inference are discussed. (Contains 4 figures, 1 table, and 1 footnote.)
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A