Extending Cognitive Models to Account for Individual Differences

扩展认知模型以考虑个体差异

• 批准号: DP0451793
• 负责人: A/Prof Danielle Navarro
• 金额: $ 10.28万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2004
• 资助国家: 澳大利亚
• 起止时间: 2004-09-22 至 2007-09-21
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0451793
• 关键词: Extending; Cognitive; Models; Account; Individual

Despite their impressive achievements, cognitive models of memory retention, category learning, and stimulus representation usually model people as ?invariants?, concentrating on what makes them the same. This project aims to extend all three types of model to also treat people as ?individuals?, and account for how people are different. Advanced model selection methods will be used to do this in a way that is complete, general, and principled. The outcome will be a set of new theoretical models, and new algorithms to learn the models from empirical data, that explain the differences between people in remembering, learning and representing information.

尽管他们令人印象深刻的成就，记忆保持，类别学习和刺激表征的认知模型通常模型的人？不变量？专注于它们的相同之处该项目旨在扩展所有三种类型的模型，使其也将人视为？个人？并解释人们是如何不同的。将采用先进的模型选择方法，以完整、通用和有原则的方式进行。结果将是一组新的理论模型，以及从经验数据中学习模型的新算法，这些模型解释了人们在记忆，学习和表征信息方面的差异。