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Modelling a Fractionated System of Deductive Reasoning over Categorical Syllogisms

Modelling a Fractionated System of Deductive Reasoning over Categorical Syllogisms

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Title: Modelling a Fractionated System of Deductive Reasoning over Categorical Syllogisms
Author: Giovannini, Gregory
Abstract: The 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.
Subject: Computer science
Keywords: Deductive reasoning
Computational modelling
Syllogism
Categorical syllogism
Reasoning
4CAPS
Psychology
Type: Electronic Thesis or Dissertation
Rights: Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
URI: http://hdl.handle.net/10315/34245
Supervisor: Goel, Vinod
Degree: MA - Master of Arts
Program: Psychology(Functional Area: Developmental Science)
Exam date: 2017-04-24
Publish on: 2018-03-01

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