Abstract. In this paper we address the problem of limited growth and the difficulty of self-repair in the field of Artificial Embryology. We implemented a topological simulation of multiple cells which is continuous, structure-oriented, with a dynamically connected network of growing cells and endogenous communication between 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 gene regulatory 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 implementations of cell death and signaling cell death on the problem of self-repair.
Streichert et al. have investigated the problems of growth regulation and self-repair in artificial embryos with a single cell type using Random Boolean Networks and S-Systems REF .
Evolving the Ability of Limited Growth and Self-Repair for Artificial Embryos
In Advances in Artificial Life - Proceedings of the 7th European Conference on Artificial Life
Computer Science