Suppr超能文献

熟悉度匹配:关系比较任务的一种生态理性启发式方法。

Familiarity-Matching: An Ecologically Rational Heuristic for the Relationships-Comparison Task.

机构信息

Graduate School of Arts and Sciences, The University of Tokyo.

Department of Psychology, Yasuda Women's University.

出版信息

Cogn Sci. 2020 Feb;44(2):e12806. doi: 10.1111/cogs.12806.

Abstract

Previous studies have shown that people often use heuristics in making inferences and that subjective memory experiences, such as recognition or familiarity of objects, can be valid cues for inferences. So far, many researchers have used the binary choice task in which two objects are presented as alternatives (e.g., "Which city has the larger population, city A or city B?"). However, objects can be presented not only as alternatives but also in a question (e.g., "Which country is city X in, country A or country B?"). In such a situation, people can make inferences based on the relationship between the object in the question and each object given as an alternative. In the present study, we call this type of task a "relationships-comparison task." We modeled the three inference strategies that people could apply to solve it (familiarity-matching [FM; a new heuristic we propose in this study], familiarity heuristic [FH], and knowledge-based inference [KI]) to examine people's inference processes. Through Studies 1, 2, and 3, we found that (a) people tended to rely on heuristics, and that FM (inferences based on similarity in familiarity between objects) well explained participants' inference patterns; (b) FM could work as an ecologically rational strategy for the relationships-comparison task since it could effectively reflect environmental structures, and that the use of FM could be highly replicable and robust; and (c) people could sometimes use a decision strategy like FM, even in their daily lives (consumer behaviors). The nature of the relationships-comparison task and human cognitive processes is discussed.

摘要

先前的研究表明,人们在进行推理时经常使用启发式,并且对物体的主观记忆体验(如对物体的识别或熟悉程度)可以作为推理的有效线索。到目前为止,许多研究人员已经使用了二元选择任务,其中两个物体被呈现为替代物(例如,“哪个城市的人口更多,城市 A 还是城市 B?”)。然而,物体不仅可以作为替代物呈现,也可以作为问题呈现(例如,“城市 X 位于哪个国家,国家 A 还是国家 B?”)。在这种情况下,人们可以根据问题中物体与每个替代物之间的关系进行推理。在本研究中,我们将这种类型的任务称为“关系比较任务”。我们构建了人们可以应用于解决它的三种推理策略(我们在本研究中提出的新启发式熟悉度匹配 [FM]、熟悉度启发式 [FH] 和基于知识的推理 [KI]),以检验人们的推理过程。通过研究 1、2 和 3,我们发现:(a)人们倾向于依赖启发式,并且 FM(基于物体之间熟悉度相似性的推理)很好地解释了参与者的推理模式;(b)FM 可以作为关系比较任务的一种生态理性策略,因为它可以有效地反映环境结构,并且 FM 的使用可以高度复制和稳健;(c)人们有时可以使用类似于 FM 的决策策略,即使在日常生活中(消费者行为)也是如此。讨论了关系比较任务的性质和人类认知过程。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验