Evolutionary intelligence: an introduction to theory and applications with Matlab

This book gives a good introduction to evolutionary computation for those whoare first entering the field and are looking for insight into the underlying mechanisms behind them. Emphasizing the scientific and machine learning applications of genetic algorithms instead of applications to optimization and engineering, the book could serve well in an actual course on adaptive algorithms. The author includes excellent problem sets, these being divided up into ‘thought exercises’ and ‘computer exercises’ in genetic algorithm. Practical use of genetic algorithms demands an understanding of how to implement them, and the author does so in the last two chapters of the book by giving the applicationsin various fields. This book also outlines some ideas on when genetic algorithms and genetic programming should be used, and this is useful since a newcomer to the field may be tempted to view a genetic algorithm as merely a fancy Monte Carlo simulation. Basic Introduction to Evolutionary Computation. Containsbasic concepts, several applications of Evolutionary Computation and solved Problems using MATLAB software and C/C++. Written for a wide range of readers, who wishes to learn the basic concepts of Evolutionary and Genetic Algorithms.A starter can understand the concepts with a minimal effort INDICE: Introduction to Evolutionary Computation.- Evolutionary Algorithms.- Genetic Algorithms with Matlab.- Genetic Programming Concepts.- Parallel Genetic Algorithms.- Applications of Evolutionary Algorithms.- Applications of Genetic Algorithms.- Genetic Programming Applications.- Applications of Parallel Genetic Algorithm.- Assembling DNA Fragments with a Distributed Genetic Algorithm.

• ISBN: 978-3-540-75158-8
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 584
• Fecha Publicación: 01/01/2008
• Nº Volúmenes: 1
• Idioma: Inglés