This paper has two main parts. In the first part, we motivate a kind of indeterminate, suppositional credences by discussing the prospect for a subjective interpretation of a causal Bayesian network (CBN), an important tool for causal reasoning in artificial intelligence. A CBN consists of a causal graph and a collection of interventional probabilities. The subjective interpretation in question would take the causal graph in a CBN to represent the causal structure that is believed by an agent, and interventional probabilities in a CBN to represent suppositional credences. We review a difficulty noted in the literature with such an interpretation, and suggest that a natural way to address the challenge is to go for a generalization of CBN that allows indeterminate credences. In the second part, we develop a decision-theoretic foundation for such indeterminate suppositional credences, by generalizing a theory of coherent choice functions to accommodate some form of act-state dependence. The upshot is a decision-theoretic framework that is not only rich enough to, so to speak, ground the probabilities in a subjectively interpreted causal network, but also interesting in its own right, in that it accommodates both act-state dependence and imprecise probabilities.
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Ann K. Boggiano Ann Shields Marty Barrett Teddy Kellam Erik Thompson Jeffrey Simons Phyllis Katz 《Motivation and emotion》1992,16(3):271-296
This paper includes research comprised of field studies and laboratory experiments to examine our diathesis-stress model that students with an extrinsic motivational orientation given evaluative/controlling directives are at risk for maladaptive achievement patterns, including performance, cognitive, and emotional deficits of helplessness. The findings, using our multimethod approach, confirmed our assumptions and indicated that motivational orientation is a more reliable predictor of helplessness than either attributions or perceptions of competence. The pattern of data obtained across studies is discussed in light of other theoretical approaches to understanding achievement patterns in students.The research reported here was supported, in part, by Grant No. MN45566 from NIMH. Address all correspondence to Ann K. Boggiano, Department of Psychology, Campus Box 345, University of Colorado, Boulder, Colorado 80309-0345. 相似文献
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