Computational and Behavioral Approaches to Cognition

认知的计算和行为方法

• 批准号: 6592682
• 负责人: LYNNE Marie REDER
• 金额: $ 18.42万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-07-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6592682
• 关键词: Computational; Behavioral; Approaches; Cognition

DESCRIPTION (provided by applicant): The purpose of the proposed predoctoral and postdoctoral programs is to train the next generation of cognitive psychologists both to develop formal computational models and to test and refine these models, by rigorously comparing the simulation data to carefully collected empirical data. The field is ready to benefit from formal, computational models of cognitive processes. The tools are being developed that enable this formalism, and the end product will not only deepen the empirical and conceptual basis of cognitive psychology, but will also provide stronger links between psychology, neuroscience, and the treatment of problems in mental health. Carnegie Mellon is especially suited to provide this next generation of cognitive scientists with these tools. There is a long tradition at CMU to strive for complete cognitive models to account for a wide range of phenomena using a small common set of theoretical assumptions. The proposed program would be our first focused on training modeling skills. One of the distinctive features of psychological research at CMU is the dual concern for experimental methodology and theoretical models, not just each in isolation. We have promoted the development of both production system (symbolic), connectionist (sub-symbolic) and hybrid models of the human information processing architecture as well as many specific models of performance in particular tasks. In all cases, the researchers have tested and refined their models based on behavioral and physiological data collected here at CMU and elsewhere. Methodologies that have been developed and refined within by our department include: the automatic coding of verbal protocols, the analysis of eye fixations while thinking and problem solving, and functional MRI measurements of higher cognitive processes. Some of these models address the data at the grain size of individual responses, with few subject-specific parameters. The program's goal is to develop skilled researchers who are both competent and comfortable combining the approaches of behavioral research with development of computationally implemented models of cognitive performance. Participation in research, both empirical and modeling, is a fundamental component of helping students achieve this goal. Formal courses and seminars play an important role as well. We will formally instruct and demonstrate the skills of comparing the data derived from a simulation to the human data collected from behavioral research, providing students with the skills to evaluate the quality of the fit and the sensitivity to know when and how to revise one's model based on these comparisons. In addition we will ensure that trainees are conversant in multiple computational approaches and recognize the strengths and weaknesses of each.

描述（由申请人提供）：拟议的博士前和博士后计划的目的是培养下一代认知心理学家，通过严格比较模拟数据和仔细收集的经验数据，开发正式的计算模型，并测试和完善这些模型。该领域已经准备好从认知过程的正式计算模型中受益。正在开发的工具，使这种形式主义，最终产品不仅将深化认知心理学的经验和概念基础，但也将提供心理学，神经科学和心理健康问题的治疗之间更强的联系。卡内基梅隆大学特别适合为下一代认知科学家提供这些工具。 CMU有一个悠久的传统，即努力建立完整的认知模型，以使用一小部分共同的理论假设来解释各种现象。该计划将是我们第一个专注于培训建模技能的计划。 CMU心理学研究的一个显着特点是对实验方法和理论模型的双重关注，而不仅仅是孤立的。我们促进了人类信息处理架构的生产系统（符号），连接主义（子符号）和混合模型的发展，以及在特定任务中的许多特定性能模型。在所有情况下，研究人员都根据CMU和其他地方收集的行为和生理数据测试和改进了他们的模型。我们部门已经开发和完善的方法包括：口头协议的自动编码，思考和解决问题时的眼睛注视分析，以及更高认知过程的功能性MRI测量。其中一些模型处理个体响应粒度的数据，很少有受试者特定的参数。 该计划的目标是培养熟练的研究人员，他们既有能力又能将行为研究方法与认知性能的计算实现模型的开发相结合。参与研究，无论是实证和建模，是帮助学生实现这一目标的基本组成部分。正式课程和研讨会也发挥着重要作用。我们将正式指导和展示比较来自模拟的数据与从行为研究收集的人类数据的技能，为学生提供评估拟合质量的技能，以及了解何时以及如何根据这些比较修改模型的灵敏度。此外，我们将确保学员熟悉多种计算方法，并认识到每种方法的优点和缺点。