INSTANCE-BASED MODELS OF LEARNING MEMORY AND JUDGMENT

基于实例的学习记忆和判断模型

• 批准号: 2241182
• 负责人: EVAN K HEIT
• 金额: $ 2.86万
• 依托单位: NORTHWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-04-06 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/2241182
• 关键词: classification; cognition; concept; judgment; learning; mathematical model; memory; model design /development; performance; stimulus /response

This project aims to improve our understanding of the basic processes of human learning and memory by developing instance-based models of memory. These models have been used to explain categorization tasks by assuming that our mental representations of categories consist of sets of category members or exemplars. Instance models are extended here to explain more complex phenomena from the areas of learning, memory, and judgment. These phenomena include reasoning from chains of examples, conceptual combination, learning relations between multiple variables, and judgment of event frequency. In experimental tests of these extended models, subjects will study examples, such as personality trait descriptions for a group of people, then make probability or classification judgments about the traits. The long-term objective of this research is to develop instance-based models into a framework that helps psychologists understand a wide range of cognitive abilities.

该项目旨在提高我们对基本流程的理解 通过开发基于实例的记忆模型来人类学习和记忆。 这些模型已用于通过假设来解释分类任务 我们对类别的心理表征由类别集组成 成员或模范。 这里扩展实例模型以解释更多 学习、记忆和判断领域的复杂现象。 这些 现象包括从一系列例子进行推理、概念性的 组合，学习多个变量之间的关系，并进行判断 事件频率。 在这些扩展模型的实验测试中，受试者 将研究示例，例如对一组人的人格特质描述 人，然后对特征做出概率或分类判断。 这项研究的长期目标是开发基于实例的 将模型纳入一个框架中，帮助心理学家理解广泛的 认知能力。

项目成果

Influences of prior knowledge on selective weighting of category members.

先验知识对类别成员选择性加权的影响。

• DOI: 10.1037//0278-7393.24.3.712
• 发表时间: 1998
• 期刊: Journal of experimental psychology. Learning, memory, and cognition
• 作者: Heit,E