The infinite population simple genetic algorithm is a discrete dynamical system model of a genetic algorithm. It is conjectured that trajectories in the model always converge to fixed points. This paper shows that an arbitrarily small perturbation of the fitness will result in a model with a finite number of fixed points. Moreover, every sufficiently small perturbation of fimess preserves the finiteness of the fixed point set. These results allow proofs and constructions that require finiteness of the fixed point set. For example, applying the stable manifold theorem to a fixed point requires the hyperbolicity of the differential of the transition map of the genetic algorithm, which requires (among other things) that the fixed point be isol...
This paper was written while Alden Wright was visiting the School of Computer Science, University of...
AbstractIn the classical model of population genetics for continuous time (Fisher's equation) for n ...
A common problem to all applications of linear finite dynamical systems is analyzing the dynamics wi...
The infinite population simple genetic algorithm is a discrete dynamical system model of a genetic a...
AbstractWe study an infinite population model for the genetic algorithm, where the iteration of the ...
In the Infinite Population Simple Genetic Algorithm, stability of fixed points is considered when mu...
ABSTRACT The Vose dynamical system model of the simple genetic algorithm models the behavior of this...
Considerable empirical results have been reported on the computational performance of genetic algori...
summary:Evolutionary Algorithms, also known as Genetic Algorithms in a former terminology, are proba...
Evolutionary Algorithms, also known as Genetic Algorithms in a former terminology, are probabilistic...
Convergence of genetic algorithms in the form of asymptotic stability requirements is discussed. Som...
A general form of stochastic search is described (random heuristic search), and some of its general ...
Evolutionary algorithms are general purpose optimization algorithms. Despite their successes in many...
textabstractInfinite population models show a deterministic behaviour. Genetic algorithms with finit...
AbstractMetastability is a common phenomenon. Many evolutionary processes, both natural and artifici...
This paper was written while Alden Wright was visiting the School of Computer Science, University of...
AbstractIn the classical model of population genetics for continuous time (Fisher's equation) for n ...
A common problem to all applications of linear finite dynamical systems is analyzing the dynamics wi...
The infinite population simple genetic algorithm is a discrete dynamical system model of a genetic a...
AbstractWe study an infinite population model for the genetic algorithm, where the iteration of the ...
In the Infinite Population Simple Genetic Algorithm, stability of fixed points is considered when mu...
ABSTRACT The Vose dynamical system model of the simple genetic algorithm models the behavior of this...
Considerable empirical results have been reported on the computational performance of genetic algori...
summary:Evolutionary Algorithms, also known as Genetic Algorithms in a former terminology, are proba...
Evolutionary Algorithms, also known as Genetic Algorithms in a former terminology, are probabilistic...
Convergence of genetic algorithms in the form of asymptotic stability requirements is discussed. Som...
A general form of stochastic search is described (random heuristic search), and some of its general ...
Evolutionary algorithms are general purpose optimization algorithms. Despite their successes in many...
textabstractInfinite population models show a deterministic behaviour. Genetic algorithms with finit...
AbstractMetastability is a common phenomenon. Many evolutionary processes, both natural and artifici...
This paper was written while Alden Wright was visiting the School of Computer Science, University of...
AbstractIn the classical model of population genetics for continuous time (Fisher's equation) for n ...
A common problem to all applications of linear finite dynamical systems is analyzing the dynamics wi...