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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.
Awakener aims to provide a Java library for solving practical, real world optimisation problems by means of genetic algorithms (turnkey algorithms for >= 90% of industry problems). Awakener extends Sleepwalker with specific algorithms.
Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.
Data types and utility classes for use with evolutionary algorithms.
EZvolve Foundation Classes is a set of data types and utility classes for use with evolutionary algorithms. Currently implemented support for bit string encoding, populations, fitnesses, fitness functions, probabilities, and probability vectors.
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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.
http://jocdelavida.piposerver.com - Online implementation of Conway's Game of the Life 0 players game, but using entities based on the nature, like animals or plants who born, grow up, reproduces breed and die. Written in Java 6 and Adobe Flex 3.
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.
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.
Don't hard-code data-structures for Artificial Intelligence (AI). Evolve them (and control flow) as cycles of arrays in arrays with size constraints based on other array sizes (at specific index) in terms of range, multiply, exponent, or permutation. No working code yet. Whats there now is an extension of GigaLineCompile which would become part of Human AI Net, but there are other projects to finish before I can come back to this one.
CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.
This chess program changes its strength to give the best match against you. Eventually it learns to beat you specifically through learning alogirthms. Features included transposition tables and a elementary 3-piece endgame tablebase.
Origin is a evolver for the programming game Corewars. Part of this project is a modified MARS (Memory Array Redcode Simulator) written in C especialy for evolvers. With SWIG its going to be very easy to use in different languages.
The Gene Expression Programming Framework in Java.
It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.
OW.NET -- 1-Wire API port from Java (and J#) to C#. Use the Dallas 1-Wire and iButton chips with standard C# using a serial adapter (also CF.net) or the TMEX drivers on the Windows platform. No J# distribution installation required.
An attempt to design minimum cost broadband networks with the use of a modified version of the Particle Swarm Optimization method. A GIS subsystem is used for the visualization of data and results.
A simulation environment for 2D robots to interact and perform tasks in. Meant to be educational and demonstrate emergent behaviors. No download necessary! See demos on project website!
The Distributed Genetic Programming Framework is a scalable Javagenetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.
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.
OAP Lite is Optimized Algorithms Platform Lite, which simplifies the process of solving some optimization problems by Genetic Algorithms. It is a highly configurable, efficient tool for user to get the optimum result without programming.