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Related Experiment Video

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Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task

Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task

Published on: July 22, 2025

Model fitting data from syllogistic reasoning experiments.

Masasi Hattori¹

¹College of Comprehensive Psychology, Ritsumeikan University, Ibaraki, Osaka 567-8570, Japan.

|November 23, 2016

Summary

This summary is machine-generated.

This study integrates mental models and heuristics in syllogistic reasoning using probabilistic models. It provides predicted data and model fitting results for 12 experiments, with R source code available.

Keywords:

Deduction Information gain Mental representation Probabilistic inference Syllogistic reasoning Symmetry inference

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Area of Science:

Cognitive Science
Psychology
Artificial Intelligence

Background:

Syllogistic reasoning is a key area in cognitive science.
Existing theories often focus on either mental models or heuristics.
A unified probabilistic framework is needed to explain reasoning processes.

Purpose of the Study:

To present predicted data from three probabilistic models of syllogistic reasoning.
To provide model fitting results for 12 published experiments.
To offer a computational framework integrating mental models and heuristics.

Main Methods:

Utilized three signature probabilistic models of syllogistic reasoning.
Performed model fitting against data from 12 empirical experiments (N=404).
Implemented computational models in R, providing source code.

Main Results:

Presented predicted data aligning with empirical findings.
Demonstrated model fitting success across a range of syllogistic reasoning experiments.
Quantified the performance of probabilistic models in explaining human reasoning.

Conclusions:

Probabilistic models offer a viable approach to integrating mental models and heuristics.
The provided data and code facilitate further research in computational cognitive science.
This work advances the understanding of deductive reasoning and cognitive modeling.