Emergent computation
Computation at the edge of Chaos: phase transitions and emergent computation
Emergent computation
Building Complex Systems Using Developmental Process: An Engineering Approach
ICES '98 Proceedings of the Second International Conference on Evolvable Systems: From Biology to Hardware
Cellular Automata
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Towards Development on a Silicon-based Cellular Computing Machine
Natural Computing: an international journal
Generating large-scale neural networks through discovering geometric regularities
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Self-modifying cartesian genetic programming
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Environment as a spatial constraint on the growth of structural form
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Measures of complexity for artificial embryogeny
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A cellular model for the evolutionary development of lightweight material with an inner structure
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A dynamical systems perspective on agent-environment interaction
Artificial Intelligence
Biologically inspired evolutionary development
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
Discrete dynamics of cellular machines: specification and interpretation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Genome parameters as information to forecast emergent developmental behaviors
UCNC'12 Proceedings of the 11th international conference on Unconventional Computation and Natural Computation
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In this work we target to measure genomic properties in EvoDevo systems as to predict phenotypic properties related to the emergence of artificial organisms. We propose a measurement, λ d, based on the composition of the genome, that can give prediction on how the emerging organism will develop. The experimental approach uses a minimalistic developmental model. The result show that the parameter λ d can predict phenotypic properties. The aim of introducing a parameter like λ d is to get more knowledge on the relation between genomic properties and phenotypic properties of developing organisms.