Date of Award
Gras, Robin (School of Computer Science)
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
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.
Aspinall, Adam, "K-Means Clustering as a Speciation Mechanism within an Individual-Based Evolving Predator-Prey Ecosystem Simulation" (2010). Electronic Theses and Dissertations. 315.