Sufficiency and Necessity Assumptions in Causal Structure Induction

Autor/inn/en	Mayrhofer, Ralf; Waldmann, Michael R.
Titel	Sufficiency and Necessity Assumptions in Causal Structure Induction
Quelle	In: Cognitive Science, 40 (2016) 8, S.2137-2150 (14 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0364-0213
DOI	10.1111/cogs.12318
Schlagwörter	Causal Models; Bayesian Statistics; Inferences; Probability; Logical Thinking + Suchen Sie Ihr Suchwort? Kausalanalyse; Inference; Inferenz; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie
Abstract	Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when deciding between alternative causal structures. In three experiments, we requested subjects to choose which of two observable variables was the cause and which the effect. We found strong evidence that learners have interindividually variable but intraindividually stable priors about causal parameters that express a preference for causal determinism (sufficiency or necessity; Experiment 1). These priors predict which structure subjects preferentially select. The priors can be manipulated experimentally (Experiment 2) and appear to be domain-general (Experiment 3). Heuristic strategies of structure induction are suggested that can be viewed as simplified implementations of the priors. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01