MSc Thesis Defence - Alex Bailey

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The Department of Computer Science announces the thesis defence of Mr. Alexander Bailey titled "Automatic Inference of Graph Models for Complex Networks with Genetic Programming".

When: May 30, 1:00 pm

Where: WH 147

Examining Committee;

Dr. Rick Cheel, Chair of Examination Committee

Dr. Shahryar Rahnamayan, External Examiner, University of Ontario Institute of Technology

Dr. Beatrice Ombuki-Berman, Supervisor

Dr. Mario Ventresca, Supervisor

Dr. Brian Ross

Dr. Ke Qui

Abstract

Complex networks arise naturally and spontaneously from all things that act as a part of a larger system. From patterns of socialization between people, to the way biological systems organize themselves, complex networks are ubiquitous, although currently they are poorly understood. Algorithms, designed by humans have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology,neuroscience, telecommunications, and the social sciences have resulted. The algorithms, called graph models, are non-trivial to design, represent significant human effort, and may only be accurate for specific phenomena. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, it is the first application of Genetic Programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.