Evolving the ability of limited growth and self-repair for artificial embryos

Abstract

In this paper we address the problem of limited growth and the difficulty of self-repairing in the field of Artificial Embryology. For this purpose, we developed a topological simulation environment for multiple cells which is continuous and structure-oriented, with a dynamically connected network of growing cells and endogenous communication between these cells. The cell behavior is simulated based on models of gene regulatory networks like Random Boolean Networks and S-Systems. Evolutionary Algorithms are used to evolve and optimize the parameters of the models of the gene networks. We compare the performance of Random Boolean Networks and S-Systems when optimized by Evolutionary Algorithms on the problem of limited growth and two types of cell death with and without signaling of cell death on the problem of self-repair.