We have collection of more than 1 Million open source products ranging from Enterprise product to
small libraries in all platforms. We aggregate information from all open source repositories.
Search and find the best for your needs. Check out projects section.
Read the research paper BF-Programmer: A Counterintuitive Approach to Autonomously Building Simplistic Programs Using Genetic Algorithms. AI-Programmer is an experiment with using artificial intelligence and genetic algorithms to automatically generate programs. Successfully created programs by the AI include: hello world, hello , addition, subtraction, reversing a string, fibonnaci sequence, 99 bottles of beer on the wall, and more. It's getting smarter. In short, it's an AI genetic algorithm implementation with self modifying code.
GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). Can be used in any kind of .NET Core and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Web Forms, UWP, Windows Forms, GTK#, Xamarin and Unity3D games.
Evo is easy to use and extend library for evolutionary computation. It contains either traditional evolutionary algorithms and more complicated, modern genetic/evolutionary algorithms and operators. Implemented in C#.
The Shared Genomics project has developed parallelised statistical applications (MPI/OpenMP) which can analyse large genomic data-sets containing thousands of Single Nucleotide Polymorphisms (SNP). The code is based on the popular PLINK SNP-analysis program.
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are more focused on artificial model's of biological computation, such as Hopfield Neural Networks, while others are inherently more biologically-focused, such as the basic genetic programming module included in this project. Use it for whatever you like, and please contribute back to the project by cleaning up code that is here or contributing new code for applications in biology that you may find interesting to program. Below you will find several categories of applications in this project.
pyTSP uses various approaches to solve the TSP (linear programming, construction heuristics, optimization heuristics, genetic algorithm). It provides a geographical step-by-step visualization of each of these algorithms.
This is the Xcode Playground to accompany the book Classic Computer Science Problems in Swift by David Kopec. The book is available for purchase directly from the publisher, Manning, and from other book vendors. The Playground is compatible with Swift 4 (Xcode 9).