Evolution of Parallel Cellular Machines: The Cellular Programming Approach
Evolution of Parallel Cellular Machines: The Cellular Programming Approach
Development Brings Scalability to Hardware Evolution
EH '05 Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware
How artificial ontogenies can retard evolution
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
A dynamical systems perspective on agent-environment interaction
Artificial Intelligence
A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems
IEEE Transactions on Evolutionary Computation
VLSI implementations of threshold logic-a comprehensive survey
IEEE Transactions on Neural Networks
Phenotypic, developmental and computational resources: scaling in artificial development
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Instruction-based development: From evolution to generic structures of digital circuits
International Journal of Knowledge-based and Intelligent Engineering Systems - Adaptive Hardwarel / Evolvable Hardware
Evolution, development and learning using self-modifying cartesian genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Augmenting artificial development with local fitness
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Cell2Organ: self-repairing artificial creatures thanks to a healthy metabolism
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolving plastic responses in artificial cell models
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Discrete dynamics of cellular machines: specification and interpretation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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Biological organisms have an inherent ability to respond to environmental changes. The response can emerge as organisms that can develop to structural and behavioural different phenotypes. The cue to what phenotypic property to express is cued by the environment. This implies that the information necessary for a single genotype to develop to different phenotypes is the genome itself and the information provided by the environment i.e. phenotypic plasticity. This concept is incorporated in the development model presented herein so as to demonstrate how an evolved genome can express different phenotypes depending on the present environment which the phenotype has to develop and survive in. An experimental approach is used to show the concept to evolved robust behaviour in different environments and to evolve genomes that can be triggered to express different behaviour depending on the present environment.