{"title":"A Boolean generalization of the information-gain model can eliminate specific reasoning errors","authors":"Chris Thornton","doi":"10.1016/j.jmp.2025.102918","DOIUrl":null,"url":null,"abstract":"<div><div>In the Wason selection task, subjects show a tendency towards counter-logical behaviour. Evidence gained from this experiment raises questions about the role that deductive logic plays in human reasoning. A prominent explanation of the effect uses an information-gain model. Rather than reasoning deductively, it is argued that subjects seek to reduce uncertainty. The bias that is observed is seen to stem from maximizing information gain in this adaptively rational way. This theoretical article shows that a Boolean generalization of the information-gain model is potentially considered the normative foundation of reasoning, in which case several inferences traditionally considered errors are found to be valid. The article examines how this affects inferences involving both over-extension of logical implication and overestimation of conjunctive probability.</div></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"125 ","pages":"Article 102918"},"PeriodicalIF":2.2000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematical Psychology","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022249625000197","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
In the Wason selection task, subjects show a tendency towards counter-logical behaviour. Evidence gained from this experiment raises questions about the role that deductive logic plays in human reasoning. A prominent explanation of the effect uses an information-gain model. Rather than reasoning deductively, it is argued that subjects seek to reduce uncertainty. The bias that is observed is seen to stem from maximizing information gain in this adaptively rational way. This theoretical article shows that a Boolean generalization of the information-gain model is potentially considered the normative foundation of reasoning, in which case several inferences traditionally considered errors are found to be valid. The article examines how this affects inferences involving both over-extension of logical implication and overestimation of conjunctive probability.
期刊介绍:
The Journal of Mathematical Psychology includes articles, monographs and reviews, notes and commentaries, and book reviews in all areas of mathematical psychology. Empirical and theoretical contributions are equally welcome.
Areas of special interest include, but are not limited to, fundamental measurement and psychological process models, such as those based upon neural network or information processing concepts. A partial listing of substantive areas covered include sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation.
The Journal of Mathematical Psychology is affiliated with the Society for Mathematical Psychology.
Research Areas include:
• Models for sensation and perception, learning, memory and thinking
• Fundamental measurement and scaling
• Decision making
• Neural modeling and networks
• Psychophysics and signal detection
• Neuropsychological theories
• Psycholinguistics
• Motivational dynamics
• Animal behavior
• Psychometric theory