The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
State Aggregation and Population Dynamics in Linear Systems
Artificial Life
Schemata evolution and building blocks
Evolutionary Computation
State Aggregation and Population Dynamics in Linear Systems
Artificial Life
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
Theory of the simple genetic algorithm with α-selection
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Intrinsic System Model of the Genetic Algorithm with α-Selection
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Neighborhood graphs and symmetric genetic operators
FOGA'07 Proceedings of the 9th international conference on Foundations of genetic algorithms
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Coarse graining is defined in terms of a commutative diagram. Necessary and sufficient conditions are given in the continuously differentiable case. The theory is applied to linear coarse grainings arising from partitioning the population space of a simple Genetic Algorithm (GA). Cases considered include proportional selection, binary tournament selection, and mutation. A nonlinear coarse graining for ranking selection is also presented. Within the context of GAs, the primary contribution made is the introduction and illustration of a technique by which the possibility for coarse grainings may be analyzed. A secondary contribution is that a number of new coarse graining results are obtained.