Effects of Group Composition and Level of Selection in the Evolution of Cooperation in Artificial Ants

Since ants and other social insects have long generation time, it is very difficult for biologists to study the origin of complex social organization by guided evolution (a process where the evolution of a trait can be followed during experimental evolution). Here we use colonies of artificial ants implemented as small mobile robots with simple vision and communication abilities to explore these issues. In this paper, we present results concerning the role of relatedness (genetic similarity) and levels of selection (individual and colony-level selection) on the evolution of cooperation and division of labor in simulated ant colonies. In order to ensure thorough statistical analysis, the evolutionary experiments, herein reported, have been carried out using “minimalist” simulations of the collective robotics evolutionary setup. The results show that altruistic behaviors have low probability of emerging in heterogeneous colonies evolving under individual-level selection and that colonies with high genetic relatedness display better performance.

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