可扩展的认知模型:把西蒙(1969)的蚂蚁放回海滩。

IF 1.1 4区 心理学 Q4 PSYCHOLOGY, EXPERIMENTAL
Brendan T Johns, Randall K Jamieson, Michael N Jones
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引用次数: 1

摘要

认知建模的一个经典目标是整合过程和表征,形成完整的人类认知理论(Estes, 1955)。西蒙(1969)的开创性工作最好地概括了这一目标,他提出了蚂蚁的寓言,以描述在构建认知理论时理解一个人所处环境的重要性。然而,计算认知模型中表征作用的典型假设并不能准确地表征记忆的内容(Johns & Jones, 2010)。机器学习和认知大数据方法的最新发展,在这里被称为尺度认知建模,为过程和表征的整合提供了一个潜在的解决方案。本文将回顾认知建模中的标准实践和假设,新的大数据和机器学习方法如何修改这些实践,以及未来研究应该采取的方向。本文的目标是将认知科学中出现的大数据和机器学习方法根植于经典的认知理论原则中,为认知理论与先进的计算方法的整合提供一条建设性的途径。(PsycInfo数据库记录(c) 2023 APA,版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scalable cognitive modelling: Putting Simon's (1969) ant back on the beach.

A classic goal in cognitive modelling is the integration of process and representation to form complete theories of human cognition (Estes, 1955). This goal is best encapsulated by the seminal work of Simon (1969) who proposed the parable of the ant to describe the importance of understanding the environment that a person is embedded within when constructing theories of cognition. However, typical assumptions in accounting for the role of representation in computational cognitive models do not accurately represent the contents of memory (Johns & Jones, 2010). Recent developments in machine learning and big data approaches to cognition, referred to as scaled cognitive modelling here, offer a potential solution to the integration of process and representation. This article will review standard practices and assumptions that take place in cognitive modelling, how new big data and machine learning approaches modify these practices, and the directions that future research should take. The goal of the article is to ground big data and machine learning approaches that are emerging in the cognitive sciences within classic cognitive theoretical principles to provide a constructive pathway towards the integration of cognitive theory with advanced computational methodology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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来源期刊
CiteScore
2.30
自引率
7.70%
发文量
40
期刊介绍: The Canadian Journal of Experimental Psychology publishes original research papers that advance understanding of the field of experimental psychology, broadly considered. This includes, but is not restricted to, cognition, perception, motor performance, attention, memory, learning, language, decision making, development, comparative psychology, and neuroscience. The journal publishes - papers reporting empirical results that advance knowledge in a particular research area; - papers describing theoretical, methodological, or conceptual advances that are relevant to the interpretation of empirical evidence in the field; - brief reports (less than 2,500 words for the main text) that describe new results or analyses with clear theoretical or methodological import.
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