Proceedings of the Annual Meeting of the Cognitive Science Society

Psychologists have studied syllogistic inferences for morethan a century, but no extant theory gives an adequate accountof them. Reasoners appear to reason using different strategies.A complete account of syllogisms must therefore explainthese strategies and the resulting differences from oneindividual to another in the patterns of conclusions that theydraw. We propose a dual-process theory that solves these twoproblems. It is based on the manipulation of mental models,i.e., iconic simulations of possibilities. We also propose a newway in which to analyze individual differences, whichdepends on implementing a stochastic computer program. Theprogram, mReasoner, generates an initial conclusion bybuilding and scanning a mental model. It can vary fourseparate factors in the process: the size of a model, itscontents, the propensity to consider alternative models, andthe propensity to revise its heuristic conclusions. The formertwo parameters control intuitive processes and the latter twocontrol deliberative processes. The theory accounts forindividual differences in an early study on syllogisms(Johnson-Laird & Steedman, 1978). The computational modelprovides an algorithmic account of the different processes onwhich three subsets of participants relied (Simulation 1). Italso simulates the performance of each individual participantin the study (Simulation 2). The theory and itsimplementation constitute the first robust account ofindividual differences in syllogistic reasoning.