Algorithmes Génétiques - Genetic Algorithms - Machine Learning

in Genetic Algorithms and Evolutionary Computation: Publications

Under the direction of Kenneth A. De Jong, the Genetic Algorithms Group (GAG) at George Mason University in Fairfax, Virginia

The electronic appendix to the hitch-hiker's guide to evolutionary computation

We study the hereditary information that makes plants different from other organisms and from one another. The importance of plants to sustaining humanity is reflected by the many ecosystem services they provide us, including oxygen, medicines, food, feed, fiber, fuel, erosion and flooding control, soil regeneration, and other benefits. Following closely on the success of the Human Genome Project, plant genomics is entering a Golden Era, with many exciting new opportunities to better understand the world around us and provide in a sustainable manner for the needs of humanity.

This page was originally created by Adam Fraser at Salford UniversityAdil Qureshi.

currently maintain 221 data sets as a service to the machine learning community. You may view all data sets through our searchable interface. Our old web site is still available, for those who prefer the old format. For a general overview of the Repository, please visit our About page. For information about citing data sets in publications, please read our citation policy. If you wish to donate a data set, please consult our donation policy. For any other questions, feel free to contact the Repository librarians. We have also set up a mirror site for the Repository.

A source of information about the field of genetic programming

Reinforcement Learning

a library of routines for use in constructing process-oriented, discrete-event simulation models.

WebSim is a (freeware) simulator for learning algorithms, function approximators, and gradient descent methods. It is implemented as a set of Java classes by Leemon Baird, Mance Harmon, Scott Weaver, and Ansgar Laubsch.

Echo is a simulation tool developed to investigate mechanisms which regulate diversity and information-processing in systems comprised of many interacting adaptive agents, or complex adaptive systems (CAS)

archive for the Genetic Programming mailing list. Source code submitted to the archive are located in the code subdirectory and papers are in the papers subdirectory

This gives a list of all known EA software packages available to the public. The list was originally maintained by Nici Schraudolph. In June '93 it was agreed that it would be incorporated into this FAQ and the responsibility for maintenance taken over by the FAQ editor.

The goal is to arrange the numbers from 1 to N^2 within a NxN grid in such a way, that the sum of all rows, the sum of all columns and the sums of both diagonals become equal, i.e. the goal is to find a true magic square.

International Conference On Evolutionary Computation Jerusalem, Israel October 9-14, 1994 ftp demos

GAV est une applet de démonstration du fonctionnement d'un Algorithme Génétique (AG). Elle a pour objectif de montrer la puissance des AG et les principaux mécanismes utilisés, tout en permettant une certaine forme de visualisation du fonctionnement général. Le problème posé consiste à retrouver le génome d'un Biomorph donné (pour plus d'informations sur les Biomorphs, voir Biomorph Viewer).

lip6.fr

Alain Gogniat

Jean-Paul Davalan

Factorisation des mots. Détermination d'un morphisme pour lequel le mot est (le préfixe d') un point fixe.

Exemple écrit en javascript et permettant de retrouver, entre autres, le morphisme (substitution) 0->01 1->10 pour lequel le mot 01101001100101... de Thue-Morse est un point fixe.

Imperial College Management School

OR-Library is a collection of test data sets for a variety of Operations Research (OR) problems.

B. Leblanc, E. Lutton, and J.-P. Allouche.

Lecture Notes in Computer Science (Artificial Evolution, 1997, Eds. J.-K. Hao, E. Lutton, E. Ronald, M. Schoenauer, D. Snyers) 1363 (1998), pp. 157-166.

Bibliographie J.-P. Allouche

Stanford University John R. Koza

Statistics and Computing Volume 4, pp. 65-85, 1994.

Genetic Algorithms in Engineering and Computer Science. G. Winter, J. Periaux, M. Galan and P. Cuesta, eds. pp: 203-216, John Wiley, 1995.

Richard S. Sutton and Andrew G. Barto

MIT Press, Cambridge, MA, 1998 A Bradford Book

Marc-Michel Corsini Bordeaux

The images following are frames of a short animation sequence titled "TEXTURES" created by the author. The sequence has been generated using GP with an interactive selection mechanism.

This page is about variations, an algorithmic composition system developed by meInstruments

(short for Genetic Jammer) is an interactive genetic algorithm that learns to play jazz solos. It may well be the only evolutionary algorithm that is a "working musician."

Hitch-Hiker's Guide to Evolutionary Computation

(FAQ for comp.ai.genetic) Issue 8.1, 29 March 2000 edited by Jörg Heitkötter

(FAQ for comp.ai.genetic) Issue 9.1, 12 April 2001

Machine learning is the idea that systems are capable of learning from experience and improving over time. The possibility of creating systems that function as autonomous and cognitive units could lead to applications such as the ability to detect credit card fraud, natural language articulation, and even independent robot movement. The approach to machine learning begins with an understanding of the different types of learning and the methods used.

Directory for information about Genetic Programming, Artificial Intelligence, Genetic Algorithms, Evolutionary Computation and robotics. Includes conferences, researchers, journals, software, papers and more.

Ariel Dolan