Genetics used to be my favorite part of biology because of its elegant and broadly applicable models. I wondered if many biological phenomena can be explained and reproduced using simple rules. For this project, I used agent-based models to simulate the movement, growth, and reproduction of autonomous entities called “critters” and their collaborative or competitive interactions. Critters were visualized as polygons of different shapes, sizes, and colors to represent their phenotypes, i.e., observable traits of the entities, and foods in the environment were shown as gray disks. Over time, the critters mutate and are selected to be more agile and have a slower metabolism at the population level, reflecting the process of evolution. Moreover, bunching of similar critters non-hostile to each other, an emergent behavior, was also observed, evoking the concept of multicellularity