Sufficiency and Necessity Assumptions in Causal Structure Induction

被引:8
|
作者
Mayrhofer, Ralf [1 ]
Waldmann, Michael R. [1 ]
机构
[1] Univ Gottingen, Dept Psychol, Gosslerstr 14, D-37073 Gottingen, Germany
关键词
Bayes nets; Causal learning; Causal induction; Structure induction; COVARIATION; INFORMATION; MODEL; INTERVENTIONS; INFERENCES; NETWORKS; CHILDREN; GUIDE; TIME;
D O I
10.1111/cogs.12318
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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.
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页码:2137 / 2150
页数:14
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