A Taxonomy for artificial embryogeny
Artificial Life
EH '05 Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware
2005 Special Issue: A regenerating spiking neural network
Neural Networks - 2005 Special issue: IJCNN 2005
Evolving modular genetic regulatory networks
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
The evolutionary emergence of intrinsic regeneration in artificial developing organisms
BioADIT'06 Proceedings of the Second international conference on Biologically Inspired Approaches to Advanced Information Technology
Robust multi-cellular developmental design
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A Multi-cellular Developmental System in Continuous Space Using Cell Migration
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part I
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It has been suggested that evolving developmental programs instead of direct genotype-phenotype mappings may increase the scalability of Genetic Algorithms Many of these Artificial Embryogeny (AE) models have been proposed and their evolutionary properties are being investigated One of these properties concerns the fault-tolerance of at least a particular class of AE, which models the development of artificial multicellular organisms It has been shown that such AE evolves designs capable of recovering phenotypic faults during development, even if fault-tolerance is not selected for during evolution This type of adaptivity is clearly very interesting both for theoretical reasons and possible robotic applications. In this paper we provide empirical evidence collected from a multicellular AE model showing a subtle relationship between evolution and development These results explain why developmental fault-tolerance necessarily emerges during evolution.