The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
Artificial Life
Group properties of crossover and mutation
Evolutionary Computation
Schemata evolution and building blocks
Evolutionary Computation
Coarse graining selection and mutation
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Strong recombination, weak selection, and mutation
Proceedings of the 8th annual conference on Genetic and evolutionary computation
ACM SIGACT News
Differentiable coarse graining
Theoretical Computer Science - Foundations of genetic algorithms
IEEE Transactions on Evolutionary Computation
Coarse graining selection and mutation
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
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We consider complex systems that are composed of many interacting elements, evolving under some dynamics. We are interested in characterizing the ways in which these elements may be grouped into higher-level, macroscopic states in a way that is compatible with those dynamics. Such groupings may then be thought of as naturally emergent properties of the system. We formalize this idea and, in the case that the dynamics are linear, prove necessary and sufficient conditions for this to happen. In cases where there is an underlying symmetry among the components of the system, group theory may be used to provide a strong sufficient condition. These observations are illustrated with some artificial life examples.