Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
ICAL 2003 Proceedings of the eighth international conference on Artificial life
A Taxonomy for artificial embryogeny
Artificial Life
A Gene Network Model for Developing Cell Lineages
Artificial Life
Shape homeostasis in virtual embryos
Artificial Life
A gene regulatory model for the development of primitive nervous systems
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Journal of Computational Physics
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part I
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part I
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A computational model is presented that simulates stable growth of cellular structures that are in some cases capable of regeneration. In the model, cellular growth is governed by a gene regulatory network. By evolving the parameters and structure of the genetic network using a modified evolution strategy, a dynamically stable state can be achieved in the developmental process, where cell proliferation and cell apoptosis reach an equilibrium. The results of evolution with different setups in fitness evaluation during the development are compared with respect to their regeneration capability as well as their gene regulatory network structure. Network motifs responsible for stable growth and regeneration that emerged from the evolution are also analyzed. We expect that our findings can help to gain a better understanding of the process of growth and regeneration inspired by biological systems, in order to solve complex engineering problems, such as the design of self-healing materials.