Simulating the evolution of silverfish : Evolution modelled as an evolutionary algorithm

Abstract: An area of Artificial Intelligence, used for instance in optimization, is evolutionary algorithms. By using mechanisms similar to those that cause evolution, evolutionary algorithms can improve e.g. problem solving algorithms by artificial evolution.The purpose of this study was to show that it’s possible to simulate evolution by modelling it as an evolutionary algorithm. This was achieved by simulating the evolution of silverfish’ genes in two environments with the only difference of the presence of a threat. The results were considered to be successful as the majorityof the genes which were presumed to be important for survival changed in such away. The results could be repeated between simulations indicating that random change of the genes and deterministic factors in the environment shaped the genes of the silverfish and that after simulation the silverfish were optimally fit for the environment.