Evolutionary biology in silico: explorations of adaptation in artificial populations
2017-02-23T00:01:14Z (GMT) by
The complexity, detail and diversity of life has intrigued and excited both scientist and layperson alike. How such intricate design, as that commonly found in biological life, could have come about is the subject of millennia of thought. Charles Darwin’s (1859) theory of evolution (co-discovered by Alfred Wallace) proposes a simple mechanism of change across generations, and provides a testable explanation of such design. Although united on the validity of evolution, scientists remain divided on many open questions, including the adaptive nature of traits that benefit the group at the cost of individual fitness — that is, biological altruism. Interpreting the progress of evolutionary history from the fossil record is fraught with challenges. The large gaps between fossilization events hide the transitions between species, and much of the details of the organisms themselves are lost in the process. While we can conduct experiments on living organisms in the laboratory, the temporal and spatial scales involved in evolution in nature do not lend themselves to easily controllable and repeatable experiments. The recent field of artificial life (ALife) (Langton, 1989) provides new exciting potentials for experimental exploration of evolution. Within the software medium we can create simulations of populations of artificial organisms, which are subject to evolutionary forces, existing in an artificial environment, competing with each other for the opportunity to survive and reproduce. By incorporating such simulation techniques into the studies of evolutionary biology we greatly enhance our experimental repertoire. In this thesis I show that ALife provides new experimental techniques to explore open questions in evolutionary biology. In particular, I consider questions on the adaptive nature of groups and biological altruism. Firstly, I examine the relationship between the two popular explanations of altruism, group and kin selection, demonstrating a common dependence on inclusive fitness (Hamilton, 1964). Next, I investigate an extreme form of biological altruism, genetically programmed aging. Commonly thought to be non- adaptive (Medawar, 1952; Williams, 1957; Kirkwood and Holliday, 1979), I develop my own hypothesis of adaptive aging for the sake of group diversity, confirming it in simulated worlds of hosts and parasites. Lastly, I test, and find support for, Eldredge and Gould’s (1972) claim that punctuated equilibrium, a pervasive phenomena in the fossil record, provides the foundations for a species/group selection mechanism.