NOTE: Project has been delayed due to other tasks.
Genetic Algorithms General Solver (GAGENES) is a C++ implementation of the geneticalgorithm concept.
X-GAT (XML-based GeneticAlgorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
Based on the introduction of Genetic Algorithms in the excellent book "Collective Intelligence" I have put together some python classes to extend the original concepts.
This library is a lightweight implementation of geneticalgorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.
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Game Toolbox is a C# assembly designed to facilitate the creation of games and game prototypes. It contains no graphics code, does not depend on XNA, and is Mono-compatible. It provides implementations of A*, GOAP, a geneticalgorithm, and more.
Evolutionary Structural Optimization Package (ESOP) consists of software for viewing, analyzing, and optimizing structures containing beam, truss, and membrane plate elements utilizing OpenGL and the GeneticAlgorithm (GA). Created for use in M.S. theses
This is implementation of parallelgeneticalgorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.
A .net implementation of a framework for genetic algorithms. This tool enables programmers to write the "core" of their problem and have a geneticalgorithm immediately setup for solving it.
GEP is an evolutionary algorithm for function finding. This framework is a powerful way of expressing and coding genetic-like structures and quickly finding solutions through evolution by common genetic operators.
The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A geneticalgorithm and Markov simulations are currently implemented.
The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.
PyLife is an implementation of the game of life algorithm featuring parallel programming. It uses MPI and python to achieve a consistent software architecture and reliably performance.
A concise example of the classical geneticalgorithm, with a fancy windows terminal display. Features DNA editing, save/load, customizable constraints and statistics logging.
A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
Galapagos is a GeneticAlgorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an afternoon.
musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.