Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 81-84).by Robert William Pinder.M.Eng
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
The parallel computers of the future will be both more complex and more varied than the machines of ...
Evolutionary algorithms (EAs) are modern techniques for searching complex spaces for on optimum [11]...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includ...
A parallel implementation of Genetic Programming using PVM is described. Two different topologies fo...
Evolutionary algorithms have been gaining increased attention the past few years because of their ve...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
The thesis describes design and implementation of various evolutionary algorithms, which were enhanc...
Introduction Genetic programming is a domain-independent problem-solving approach in which computer ...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical ...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
The parallel computers of the future will be both more complex and more varied than the machines of ...
Evolutionary algorithms (EAs) are modern techniques for searching complex spaces for on optimum [11]...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includ...
A parallel implementation of Genetic Programming using PVM is described. Two different topologies fo...
Evolutionary algorithms have been gaining increased attention the past few years because of their ve...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
The thesis describes design and implementation of various evolutionary algorithms, which were enhanc...
Introduction Genetic programming is a domain-independent problem-solving approach in which computer ...
Genetic algorithms are search or classification algorithms based on natural models. They present a h...
A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical ...
The main goal of this paper is to summarize the previous research on parallel genetic algorithms. We...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...