Artificial Life X: Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living SystemsLuis Mateus Rocha Proceedings from the Tenth International Conference on Artificial Life, marking two decades of interdisciplinary research in this growing scientific community.Artificial Life is an interdisciplinary effort to investigate the fundamental properties of living systems through the simulation and synthesis of life-like processes in artificial media. The field brings a powerful set of tools to the study of how high-level behavior can arise in systems governed by simple rules of interaction.This tenth volume marks two decades of research in this interdisciplinary scientific community, a period marked by vast advances in the life sciences. The field has contributed fundamentally to our understanding of life itself through computer models, and has led to novel solutions to complex real-world problems--from disease prevention to stock market prediction--across high technology and human society. The proceedings of the biennial A-life conference--which has grown over the years from a small workshop in Santa Fe to a major international meeting--reflect the increasing importance of the work to all areas of contemporary science. |
Contents
How Scalefree Typebased Networks Emerge from Instancebased Dynamics | 8 |
Evolving Biological Clocks using Genetic Regulatory Networks | 15 |
Evolution of Repressilators Using a Biologicallymotivated Model of Gene | 22 |
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Common terms and phrases
active adaptive agents algorithm allows approach Artificial average Baldwin effect behavior biological cell complex computational connections consider consists construction corresponding defined described determined direction distance distribution dynamics effect emergence environment et al evolution evolutionary evolved example experiments Figure fitness function genes genetic genome genotype given increase indicates individual initial input interaction internal language learning limited mean measure mechanism method move mutation natural networks neural neurons nodes object observed organisms parameters patterns performance phase phenotype physical population position possible present Press probability problem produced properties protein random range References replication representation represented robot rules runs selection sensors sequence shown shows signal similar simple simulation space spatial specific step strategy structure successful tion traits University values