Research on Identification of Mental System Architecture

心理系统架构识别研究

• 批准号: 8710163
• 负责人: James Townsend
• 金额: $ 10.95万
• 依托单位: Purdue Research Foundation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-09-01 至 1990-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8710163&HistoricalAwards=false
• 关键词: Research; Identification; Mental; System; Architecture

A fruitful approach to the study of human behavior is the use of the relationships between the environment, the perceptual information flow, and the consequent behavior to infer psychological structure and function, the architecture of the mental system. From this approach, psychological functions such as perception, motivation, cognition, decision making, learning, memory, and problem solving are seen as embedded in abstract models of the internal psychological states. An important approach to the modeling of these psychological functions is to do so with closed-form mathematical models (which may, of course, need to be studied at times using computer simulations). At least as important as the individual models of individual processes is the mathematical exploration of the qualitative and quantitative behavior of mental systems which exhibit particular properties. Townsend's laboratory has been, with the aid of prior NSF support, a main source of such mathematical results. This project is designed to investigate the behavior of mental systems which have the following properties: (1) information flows only forward, with no feedback loops; (2) flow is continuous, with partial information being transmitted throughout the system on a continuous basis, rather than each subprocess being completed before it sends the results on down the line; and (3) the outputs of each process are stochastic, i.e. involve elements of randomness. In addition, results will be extended to systems that meet conditions (1) and (3), but not (2). Experimental work will be directed toward discovery of qualitative properties involving reaction time and accuracy that will make it possible to identify the system architecture. Other experiments will involve exploration of theoretical results obtained recently. Finally, a mathematical model will be constructed for a recent experimental paradigm that acquires continuous measures of response tendencies. This research, though basic, impacts in an indirect way on education and on the design of machines with which people must interact.

人类行为研究的一个卓有成效的方法是利用环境、知觉信息流和随后的行为之间的关系来推断心理结构和功能，即心理系统的架构。通过这种方法，感知、动机、认知、决策、学习、记忆和解决问题等心理功能被视为嵌入到内部心理状态的抽象模型中。对这些心理功能进行建模的一个重要方法是使用封闭形式的数学模型(当然，有时可能需要使用计算机模拟进行研究)。至少与个体过程的个体模型一样重要的是，对表现出特定属性的心理系统的定性和定量行为进行数学探索。汤森的实验室在美国国家科学基金会先前的支持下，一直是此类数学结果的主要来源。该项目旨在研究具有以下特征的心理系统的行为：(1)信息只向前流动，没有反馈环；(2)流动是连续的，部分信息在连续的基础上在整个系统中传递，而不是每个子过程在向下发送结果之前完成；(3)每个过程的输出都是随机的，即包含随机性元素。此外，结果将扩展到满足条件(1)和(3)但不满足(2)的系统。实验工作将致力于发现定性属性，包括反应时间和准确性，这将使识别系统架构成为可能。其他实验将涉及对最近获得的理论结果的探索。最后，将为最近的一种实验范式构建一个数学模型，该范式获得对反应倾向的连续测量。这项研究虽然是基础性的，但对教育和人们必须与之互动的机器的设计产生了间接影响。