Open Source Windows Genetic Algorithms - Page 3

Ocean with fishes who's are learning and evolving.

A p2p filesharing application, where every1 is forced to seed for a certain period and then every1 gets to download with a guaranteed number of seeders as well, for a certain perion of time.

Formicidae is the official simulator and visualizer for the Ant-Wars competitive programming site, written in Java and SISC. The site is hosted at www.ant-wars.net.

This project is using genetics algorithms to complete scheduling tasks such as timetables for elementary / high schools etc. Currently NetBeans project with no GUI and simple HTML export.

GAKNN is a data mining software for gene annotation data. GAKNN is built with k- Nearest Neighbour algorithm optimized by the genetic algorithm. Gene annotation datasets saved under .csv or .arff formats with Gene Ontology or FunCat categorization can use GAKNN to predict gene functions.

Galapagos is a Genetic Algorithm 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.

Gamoliyas is an open source John Conway's Game of Life game totally written in DHTML (JavaScript, CSS and HTML). Uses mouse and keyboard. Very configurable. This cross-platform and cross-browser game was tested under BeOS, Linux, *BSD, Windows and other

Classroom allocation using Genetic Algorithms and restricted mutation. Developed by AIGroup: Pablo Cababie, Facundo Cancelo, Alvaro Zweig y Gabriel Barrera

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.

GeneThello (read jə-ˈne-ˈthe-lō), is an acronym for genetic othello, an othello (reversi) playing program which based on Genetic Algorithm (GA). In principle GeneThello consist of an othello program and a genetic algorithm system.

A generic implementation of STL containers and some STL algorithms. The main intent is no make this STL implementation to work with any kind of pointers defined by allocator classes, e.g. memory_mgr::offset_ptr.

NOTE: Project has been delayed due to other tasks. Genetic Algorithms General Solver (GAGENES) is a C++ implementation of the genetic algorithm concept.

This project is a genetic algorithm engine able to be reused for other projects with minimal additional programming. The genetic algorithm engine currently plays many blackjack hands for the fitness function and produces a result similar to blackjack basic strategy. To see it in action, download the zip file and run either: GABlackjack_Demo.exe     (quick)   or GABlackjack_Long.exe       (slow, but it achieves better results). The code was written in C++, using MS Visual Studio 6.0 and MS Visual Source Safe 6.0. The genetic algorithm engine supports various mutation rates, ranked parental selection, stochastic sampling parental selection, cyclic crossover, crossover at each gene, cloning the best individual each generation, and creating random individuals each generation. To use the genetic algorithm engine to search for a different problem's solution, one needs to program a fitness function, the project settings, and a few virtual functions.

This is a cross-platform framework for using Genetic Algorithms for solutions. Written in Java and uses convinient plug-in features for every phase in the genetic development, while maintaining an easy-to-use API for easy integration into applications.

This API is intended to help developers use genetic algorithms in their own java applications. GeneticLibrary.zip contains the netbeans project of the API itself. GeneticTrial.zip contains another netbeans project which is an example explaining how to use the API. docs.zip is the documentation of the API. Please take a look there, it is really helpful. I have only two request from who will use this API; USE, UPDATE AND MODIFY IT FREELY JUST NOTE THE ORIGINAL AUTHOR

GFP use Genetic Programming and LISP-like language for growing program.

GP@home is a new group/project dedicated to fully utilizing the combined concepts of genetic programming and distributed computing to improve the quality of life for all human beings. Nothing is impossible working together.

Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.

This project aims at providing a set of tools for solving the class of monodimensional packing problems (such as cutting stock, bin packing and knapsack problem) mainly using genetic algoritms.

HH-Evolver is a framework for domain-specific, hyper-heuristic evolution. HH-Evolver automates the design of domain-specific heuristics for planning domains. Hyper-heuristics generated by our tool can then be used with combinatorial search algorithms such as A* and IDA* for solving problems of the given domain.

Program for Residence Life staffs to aid in roommate pairing.

An heuristic image stitcher made to test Genetic and PSO based algorithms

This is implementation of parallel genetic algorithm 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++.

Discontinued.