| Projects on Google Code | Results 1 - 10 of 44 |
Perl, Genetic Programming, Google API
==History==
This project has evolved over the years. It started as an experiment with Perl's object oriented capabilities and Google's earlier search API. The first finished product was some sort of genetic algorithm implementation in which the genotypes wer...
The Predictor is a framework for Genetic Algorithms (GA). It is not based on the traditional notions of GA. It is intended to be a framework that can bring GA into the enterprise. It will eventually support distributed GA.
Evolutionary algorithms for my unfinished master's thesis.
geneticalgorithms,
evolutionarycomputation,
optimization,
java,
python,
multiobjective,
singleobjective,
graphbased
Trabajo práctico de la facultad para sistemas de programación no convencional de robots.
Checkout the latest source from the source section using Subversion. Packages will be made available for download when the software is at version 0.1.
To use the application, you will need to create your own Django settings.py file with the fitbeats application in the INSTALLED_APPLICATIONS list...
==About==
NEAT (NeuroEvolution of Augmenting Topologies) is a method for evolving arbitrary neural networks developed by Kenneth O. Stanley. This project aims to implement NEAT in the Python programming language.
For further information regarding general concepts and theory, please visit: [htt...
Goal of this project is to create a flexible application for solving optimization or other problems using genetics algorithms.
Program provide instruments and settings to describe your own GA: user may choose selection, crossover and mutation strategies, fittness function and stopping condition. U...
A Genetic Algorithm library inspired by Edinburgh University's pga program (using some of the same example, but without looking at their code). Written using C++ templates so that it can be extended.
A framework for comparing the search spaces that artificial embryogeny algorithms move through during evolution. This framework samples the spaces that the algorithms move through and collects statistics about how well the evolutionary algorithm is able to use the space.
http://company.yandex.ru/grant/2009/en/datasets