Theory of genetic algorithms

Theory of genetic algorithms

(i) We investigate spectral and geometric properties of the mutation-crossover operator in a genetic algorithm with general-size alphabet. By computing spectral estimates, we show how the crossover operator enhances the averaging procedure of the mutation operator in the random generator phase of the genetic algorithm. By mapping our model to the multi-set model often investigated in the litera...

Theory of Genetic Algorithms

Genetic Algorithms: Theory and Applications

FLLL 2 Preface This is a printed collection of the contents of the lecture " Genetic Algorithms: Theory and Applications " which I gave first in the winter semester 1999/2000 at the Johannes Kepler University in Linz. The reader should be aware that this manuscript is subject to further reconsideration and improvement. Corrections, complaints, and suggestions are cordially welcome. The sources ...

Game Theory Using Genetic Algorithms

In this paper we used genetic algorithms to1 find the solution of game theory. We proposed new method foe solving game theory and find the optimal strategy for player A or player B. We can benefit from the relationship between game theory and the linear programming to find the fitness function and tested this fitness function at different examples .

Theory of Genetic Algorithms with Α-selection

Genetic algorithms are random heuristic search (RHS) algorithms for adaptive systems with a wide range of applications in search, optimisation, pattern recognition and machine learning as well as signal processing. Despite their widespread use a general theory is still lacking. A promising approach is offered by the dynamical system model which describes the stochastic trajectory of a populatio...