title: Probabilistic representation in syllogistic reasoning: A theory to integrate mental models and heuristics.
abstract: This paper presents a new theory of syllogistic reasoning. The proposed model assumes there are probabilistic representations of given signature situations. Instead of conducting an exhaustive search, the model constructs an individual-based "logical" mental representation that expresses the most probable state of affairs, and derives a necessary conclusion that is not inconsistent with the model using heuristics based on informativeness. The model is a unification of previous influential models. Its descriptive validity has been evaluated against existing empirical data and two new experiments, and by qualitative analyses based on previous empirical findings, all of which supported the theory. The model's behavior is also consistent with findings in other areas, including working memory capacity. The results indicate that people assume the probabilities of all target events mentioned in a syllogism to be almost equal, which suggests links between syllogistic reasoning and other areas of cognition.
authors.affiliation: College of Comprehensive Psychology, Ritsumeikan University, Japan. Electronic address: hat@lt.ritsumei.ac.jp.
authors.forename: Masasi
authors.initials: M
authors.lastname: Hattori
mesh_terms: D000328:Adult; D005260:Female; D000066506:Heuristics; D006801:Humans; D008128:Logic; D008297:Male; D008570:Memory, Short-Term; D008960:Models, Psychological; D011336:Probability; D055815:Young Adult
keywords: Deduction; Information gain; Mental representation; Probabilistic inference; Syllogistic reasoning; Symmetry inference