Machine Learning and Individual-Based Simulation for Theoretical Biology

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We study the evolutionary process and the emergence of species in a simulated ecosystem. We have conceived EcoSim, an individual-based evolving predator-prey ecosystem simulation. The behavioral model of each individual is unique and is the outcome of the evolution process. One major and unique contribution of this tool is that it combines a behavioral, an evolutionary and a speciation mechanism. We have shown that we can fruitfully apply machine learning techniques to extract the most significant features and provide an easily understandable model to explain the main characteristics of the problem. We will add several functionalities to the simulation to allow more realistic ecological niches to emerge through the evolution of features such as the size, the strength or the perception capacities. Then, we will apply our approach to investigate two new difficult open questions using machine learning approaches to provide semantically rich models and rules that be used by biologists. Choosing an individual as a mate is governed by sexual selection. The females have special preferences for males according to their traits. What still remains controversial is the underlying genetic mechanisms that allows the evolution of female preferences. It is well known that there exist two main genetic quality benefits: good genes and compatible genes. However, the respective role of each one of them in the resulting observed genetic diversity is still not clearly understood. We will investigate multiple hypotheses using several mate choice methods. We will analyze number of different runs, varying many factors and environmental conditions, to understand in which conditions and at what cost such kind of mating strategy could be favored by evolution. Although asexual reproduction is relatively rare in eukaryotes, it has several strong advantages over sexual reproduction. In light of these advantages, it is puzzling why sexual reproduction is so prevalent. We are interested in studying how and why sexual reproduction emerged. The goal of these simulations is to determine whether there is a relationship between level of resources and environmental stressors (predators or pathogens) and mode of reproduction. We will be able to test many hypotheses in different configurations and evaluate what are the circumstances favorable to the apparition and diffusion of sexual reproduction.