PREDICTIVE AND DIAGNOSTIC LEARNING WITHIN CAUSAL-MODELS - ASYMMETRIES IN CUE COMPETITION

被引:268
|
作者
WALDMANN, MR
HOLYOAK, KJ
机构
[1] UNIV FRANKFURT,W-6000 FRANKFURT,GERMANY
[2] UNIV CALIF LOS ANGELES,LOS ANGELES,CA 90024
关键词
D O I
10.1037/0096-3445.121.2.222
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Several researchers have recently claimed that higher order types of learning, such as categorization and causal induction. can he reduced to lower order associative learning. These claims are based in part on reports of cue competition in higher order learning. apparently analogous to blocking in classical conditioning. Three experiments are reported in which subjects had to learn to respond on the basis of cues that were defined either as possible causes of a common effect (predictive learning) or as possible effects of a common cause (diagnostic learning). The results indicate that diagnostic and predictive reasoning, far from being identical as predicted by associationistic models. are not even symmetrical. Although cue competition occurs among multiple possible causes during predictive learning, multiple possible effects need not compete during diagnostic learning. The results favor a causal-model theory.
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页码:222 / 236
页数:15
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