Date of Award

2010

Degree Type

Thesis

Degree Name

M.Sc.

Department

Computer Science

First Advisor

Gras, Robin (School of Computer Science)

Keywords

Computer Science.

Rights

CC BY-NC-ND 4.0

Abstract

Although presence of individual-based modeling in ecology continues to rise, to this date, there has been little to no studies of speciation in an evolving ecosystem simulation. This thesis presents a new method for modeling speciation within a previously created individual-based evolving predator-prey ecosystem simulation. As an alternative to the classical speciation mechanism originally implemented, k-means clustering provides a more realistic method for modeling speciation that, among other things, allows for species splitting, the recreation of the species tree of life, and more in-depth analysis of speciation. This thesis introduces the predator-prey ecosystem simulation with specific emphasis on the speciation mechanism. Moreover, the k-means speciation mechanism is presented, and the improvements it provides, including improved runtime performance and better modeling of biological theories, are provided.

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