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dc.contributor.advisorGoel, Vinod
dc.creatorGiovannini, Gregory
dc.description.abstractThe study of deductive reasoning has been a major research paradigm in psychology for decades. Recent additions to this literature have focused heavily on neuropsychological evidence. Such a practice is useful for identifying regions associated with particular functions, but fails to clearly define the specific interactions and timescale of these functions. Computational modelling provides a method for creating different cognitive architectures for simulating deductive processes, and ultimately determining which architectures are capable of modelling human reasoning. This thesis details a computational model for solving categorical syllogisms utilizing a fractionated system of brain regions. Lesions are applied to formal and heuristic systems to simulate accuracy and reaction time data for bi-lateral parietal and frontotemporal patients. The model successfully combines belief-bias and other known cognitive biases with a mental models formal approach to recreate the congruency by group effect present in the human data. Implications are drawn to major theories of reasoning.
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectComputer science
dc.titleModelling a Fractionated System of Deductive Reasoning over Categorical Syllogisms
dc.typeElectronic Thesis or Dissertation Area: Developmental Science) - Master of Arts's
dc.subject.keywordsDeductive reasoning
dc.subject.keywordsComputational modelling
dc.subject.keywordsCategorical syllogism

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