Abstract
Biologists are interested in studying the relation between the genetic diversity of a population and its fitness. We adopt the notion of entropy as a measure of genetic diversity and correlate it with fitness of an evolutionary ecosystem simulation. EcoSim is a predator-prey individual based simulation which models co-evolving sexual individuals evolving in a dynamic environment. The correlation values between entropy and fitness of all the species that ever existed during the whole simulation are presented. We show how entropy strongly correlates with fitness and investigate the factors behind this result using machine learning techniques. We build a classifier based on different species’ features and successfully predict the resulting correlation value between entropy and fitness. The best features affecting the quality of classification are also being investigated.
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Khater, M., Salehi, E., Gras, R. (2011). Correlation between Genetic Diversity and Fitness in a Predator-Prey Ecosystem Simulation. In: Wang, D., Reynolds, M. (eds) AI 2011: Advances in Artificial Intelligence. AI 2011. Lecture Notes in Computer Science(), vol 7106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25832-9_43
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DOI: https://doi.org/10.1007/978-3-642-25832-9_43
Publisher Name: Springer, Berlin, Heidelberg
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