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Author : David Edward Goldberg
Publisher : Addison Wesley France
ISBN 13 : 9782879080543
Total Pages : 417 pages
Book Rating : 4.0/5 (85 download)
Download or read book Algorithmes génétiques written by David Edward Goldberg and published by Addison Wesley France. This book was released on 1994 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Pierre Bonelli
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (494 download)
Download or read book Apprentissage par algorithmes genetiques written by Pierre Bonelli and published by . This book was released on 1993 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gilles Venturini
Publisher :
ISBN 13 :
Total Pages : 264 pages
Book Rating : 4.:/5 (49 download)
Download or read book APPRENTISSAGE ADAPTATIF ET APPRENTISSAGE SUPERVISE PAR ALGORITHME GENETIQUE written by Gilles Venturini and published by . This book was released on 1994 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: DANS CETTE THESE, NOUS NOUS SOMMES INTERESSES D'UNE PART A UN PROBLEME DE CONTROLE EN ROBOTIQUE ET EN AUTOMATIQUE CARACTERISE PAR DES VARIATIONS IMPREVUES DANS LES MODELES DU ROBOT ET DE SON ENVIRONNEMENT, ET D'AUTRE PART A UN PROBLEME D'APPRENTISSAGE DE REGLES A PARTIR D'UNE BASE D'EXEMPLES COMPORTANT DE NOMBREUSES VALEURS INCONNUES. POUR CES DEUX PROBLEMES, NOUS AVONS UTILISE LES ALGORITHMES GENERIQUES, QUI SONT DES PROCEDURES D'OPTIMISATION INSPIREES DE LA SELECTION NATURELLE, EN ESSAYANT DE LES RENDRE PLUS CONTROLABLES DE MANIERE A TRAITER DES CONNAISSANCES DU DOMAINE. LE PREMIER ALGORITHME ELABORE (AGIL) EST UNE EXTENSION DES SYSTEMES DE REGLES GENETIQUES QUI APPREND DES REGLES DE CONTROLE ET ADAPTE CES REGLES AUX VARIATIONS DU SYSTEME A CONTROLER. IL A ETE TESTE SUR DES PROBLEMES SIMULES. LE DEUXIEME ALGORITHME (SIA) S'INSPIRE DES PRINCIPES DE L'ALGORITHME AQ MAIS EN UTILISANT UN ALGORITHME GENETIQUE COMME MECANISME DE RECHERCHE. IL TRAITE LES VALEURS INCONNUES SANS ESSAYER DE LES REMPLACER. IL A ETE TESTE SUR PLUSIEURS BASES DE DONNEES ET A ETE APPLIQUE A L'ANALYSE D'UN DOMAINE JUDICIAIRE. CES DEUX ALGORITHMES UTILISENT DES HEURISTIQUES EXPLICITES ET PEUVENT TRAITER DIFFERENTS TYPES DE CONNAISSANCES DU DOMAINE
Author : Éric Pellerin
Publisher :
ISBN 13 :
Total Pages : 372 pages
Book Rating : 4.:/5 (154 download)
Download or read book Méta-apprentissage des algorithmes génétiques written by Éric Pellerin and published by . This book was released on 2005 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dana Vrajitoru
Publisher :
ISBN 13 :
Total Pages : 68 pages
Book Rating : 4.:/5 (842 download)
Download or read book Apprentissage par algorithme génétique dans la recherche d'informations written by Dana Vrajitoru and published by . This book was released on 1996 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Olivier Pinchard (mathématicien).)
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (494 download)
Download or read book Algorithmes genetiques et apprentissage pour la planification de mouvements et la navigation de robots mobiles written by Olivier Pinchard (mathématicien).) and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Olivier Pinchard (mathématicien)
Publisher :
ISBN 13 :
Total Pages : 161 pages
Book Rating : 4.:/5 (494 download)
Download or read book Algorithmes génétiques et apprentissage pour la planification de mouvements et la navigation de robots mobiles written by Olivier Pinchard (mathématicien) and published by . This book was released on 1996 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Antoine Cornuéjols
Publisher : Editions Eyrolles
ISBN 13 : 2212083017
Total Pages : 837 pages
Book Rating : 4.2/5 (12 download)
Download or read book Apprentissage artificiel written by Antoine Cornuéjols and published by Editions Eyrolles. This book was released on 2011-07-07 with total page 837 pages. Available in PDF, EPUB and Kindle. Book excerpt: Les programmes d'intelligence artificielle sont aujourd'hui capables de reconnaître des commandes vocales, d'analyser automatiquement des photos satellites, d'assister des experts pour prendre des décisions dans des environnements complexes et évolutifs (analyse de marchés financiers, diagnostics médicaux...), de fouiller d'immenses bases de données hétérogènes, telles les innombrables pages du Web... Pour réaliser ces tâches, ils sont dotés de modules d'apprentissage leur permettant d'adapter leur comportement à des situations jamais rencontrées, ou d'extraire des lois à partir de bases de données d'exemples. Ce livre présente les concepts qui sous-tendent l'apprentissage artificiel, les algorithmes qui en découlent et certaines de leurs applications. Son objectif est de décrire un ensemble d'algorithmes utiles en tentant d'établir un cadre théorique pour l'ensemble des techniques regroupées sous ce terme "d'apprentissage artificiel". À qui s'adresse ce livre ? Ce livre s'adresse tant aux décideurs et aux ingénieurs qui souhaitent mettre au point des applications qu'aux étudiants de niveau Master 1 et 2 et en école d'ingénieurs, qui souhaitent un ouvrage de référence sur ce domaine clé de l'intelligence artificielle.
Author : John J. Grefenstette
Publisher : Psychology Press
ISBN 13 : 1134989733
Total Pages : 269 pages
Book Rating : 4.1/5 (349 download)
Download or read book Genetic Algorithms and their Applications written by John J. Grefenstette and published by Psychology Press. This book was released on 2013-08-21 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1987. This is the collected proceedings of the second International Conference on Genetic Algorithms held at the Massachusetts Institute of Technology, Cambridge, MA on the 28th to the 31st July 1987. With papers on Genetic search theory, Adaptive search operators, representation issues, connectionism and parallelism, credit assignment ad learning, and applications.
Author : John J. Grefenstette
Publisher : Springer Science & Business Media
ISBN 13 : 1461527406
Total Pages : 167 pages
Book Rating : 4.4/5 (615 download)
Download or read book Genetic Algorithms for Machine Learning written by John J. Grefenstette and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: The articles presented here were selected from preliminary versions presented at the International Conference on Genetic Algorithms in June 1991, as well as at a special Workshop on Genetic Algorithms for Machine Learning at the same Conference. Genetic algorithms are general-purpose search algorithms that use principles inspired by natural population genetics to evolve solutions to problems. The basic idea is to maintain a population of knowledge structure that represent candidate solutions to the problem of interest. The population evolves over time through a process of competition (i.e. survival of the fittest) and controlled variation (i.e. recombination and mutation). Genetic Algorithms for Machine Learning contains articles on three topics that have not been the focus of many previous articles on GAs, namely concept learning from examples, reinforcement learning for control, and theoretical analysis of GAs. It is hoped that this sample will serve to broaden the acquaintance of the general machine learning community with the major areas of work on GAs. The articles in this book address a number of central issues in applying GAs to machine learning problems. For example, the choice of appropriate representation and the corresponding set of genetic learning operators is an important set of decisions facing a user of a genetic algorithm. The study of genetic algorithms is proceeding at a robust pace. If experimental progress and theoretical understanding continue to evolve as expected, genetic algorithms will continue to provide a distinctive approach to machine learning. Genetic Algorithms for Machine Learning is an edited volume of original research made up of invited contributions by leading researchers.
Author : David E. Goldberg
Publisher : Pearson Education India
ISBN 13 : 9788177588293
Total Pages : 432 pages
Book Rating : 4.5/5 (882 download)
Download or read book Genetic Algorithms written by David E. Goldberg and published by Pearson Education India. This book was released on 2013-02 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, suitable for both course work and self-study, brings together for the first time, in an informal, tutorial fashion, the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields: programmers, scientists, engineers, mathematicians, statisticians and management scientists will all find interesting possibilities here. Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs. Chapter concludes with exercises and computer assignments. No prior knowledge of Gas or genetics is assumed.
Author : David Edward Goldberg
Publisher : Addison-Wesley Professional
ISBN 13 :
Total Pages : 436 pages
Book Rating : 4.3/5 (91 download)
Download or read book Genetic Algorithms in Search, Optimization, and Machine Learning written by David Edward Goldberg and published by Addison-Wesley Professional. This book was released on 1989 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.
Author : Cédric Auliac
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (494 download)
Download or read book Approches évolutionnaires pour la reconstruction de réseaux de régulation génétique par apprentissage de réseaux bayésiens written by Cédric Auliac and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: De nombreuses fonctions cellulaires sont réalisées grâce à l'interaction coordonnée de plusieurs gènes. Identifier le graphe de ces interactions, appelé réseau de régulation génétique, à partir de données d'expression de gènes est l'un des objectifs majeurs de la biologie des systèmes. Dans cette thèse, nous abordons ce problème en choisissant de modéliser les relations entre gènes par un réseau bayésien. Se pose alors la question de l'apprentissage de la structure de ce type de modèle à partir de données qui sont en général peu nombreuses. Pour résoudre ce problème, nous recherchons parmi tous les modèles possibles le modèle le plus simple, expliquant le mieux les données. Pour cela, nous introduisons et étudions différents types d'algorithmes génétiques permettant d'explorer l'espace des modèles. Nous nous intéressons plus particulièrement aux méthodes de spéciation. ces dernières, en favorisant la diversité des solutions candidates considérées, empêchent l'algorithme de converger trop rapidement vers des optima locaux. Ces algorithmes génétiques sont comparés avec différentes méthodes d'apprentissage de structure de réseaux bayésiens, classiquement utilisées dans la littérature. Nous mettons ainsi en avant la pertinence des approches evolutionnaires pour l'apprentissage de ces graphes d'interactions. Enfin, nous les comparons à une classe alternative d'algorithmes évolutionnaires qui s'avère particulièrement prometteuse : les algorithmes à estimation de distribution. Tous ces algorithmes sont testés et comparés sur un modèle du réseau de régulation de l'insuline de 35 noeuds dont nous tirons des jeux de données synthétiques de taille modeste.
Author : Jose Mira
Publisher : Springer
ISBN 13 : 3540487719
Total Pages : 890 pages
Book Rating : 4.5/5 (44 download)
Download or read book Foundations and Tools for Neural Modeling written by Jose Mira and published by Springer. This book was released on 2006-12-08 with total page 890 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes, together with its compagnion LNCS 1607, the refereed proceedings of the International Work-Conference on Artificial and Natural Neural Networks, IWANN'99, held in Alicante, Spain in June 1999. The 89 revised papers presented were carefully reviewed and selected for inclusion in the book. This volume is devoted to foundational issues of neural computation and tools for neural modeling. The papers are organized in parts on neural modeling: biophysical and structural models; plasticity phenomena: maturing, learning, and memory; and artificial intelligence and cognitive neuroscience.
Author : Agnès Braud
Publisher :
ISBN 13 :
Total Pages : 165 pages
Book Rating : 4.:/5 (495 download)
Download or read book Fouille de données par algorithmes génétiques written by Agnès Braud and published by . This book was released on 2002 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: La fouille de données est un processus visant à la découverte de connaissances potentiellement utiles, enfouies dans les bases de données. Parmi les problématiques de ce domaine, nous nous intéressons à l'apprentissage de concepts à partir d'exemples. Nous nous concentrons sur l'apprentissage de descriptions de concepts exprimées sous forme d'un ensemble de règles, et sur l'apport des algorithmes génétiques dans ce domaine.
Author : Melanie Mitchell
Publisher : MIT Press
ISBN 13 : 0262631857
Total Pages : 213 pages
Book Rating : 4.2/5 (626 download)
Download or read book An Introduction to Genetic Algorithms written by Melanie Mitchell and published by MIT Press. This book was released on 1998-03-02 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
Author : Jose Mira
Publisher : Springer Science & Business Media
ISBN 13 : 9783540660699
Total Pages : 900 pages
Book Rating : 4.6/5 (66 download)
Download or read book Foundations and Tools for Neural Modeling written by Jose Mira and published by Springer Science & Business Media. This book was released on 1999-05-19 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes, together with its compagnion LNCS 1606, the refereed proceedings of the International Work-Conference on Artificial & Neural Networks, IWANN'99, held in Alicante, Spain in June 1999. The 91 revised papers presented were carefully reviewed & selected for inclusion in the book. This volume is devoted to applications of biologically inspired artificial neural networks in various engineering disciplines. The papers are organized in parts on artificial neural nets simulation & implementation, image processing & engineering applications.
