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Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning.
It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules".
Implemented Modules
Evolutionary Algorithms:
- CMA-ES
- (1+1)-ES
- Differential Evolution
Deterministic optimization algorithm:
- SIMPLEX
Learning:
- a simple Artificial Neural Net
Optimization problems:
- test functions
- interface for executing other programs (solvers)
- parallel execution of problems
- distributed execution of problems via socket connection between computers
Others:
- data storage
- data analyser and viewer
Evokit is an integrated environment for developing evolutionary computation algorithms. It is built around Java and the Eclipse platform, and will support several different libraries including ECJ.
libconhash is a consistent hashing libraray, which can be compiled both on Windows and Linux platform. High performance, easy to use, and easy to scale according to node's processing capacity.
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++.
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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.
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
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.
This project's goal is to implement Artificial Inteligence algorithms and make them available for any platform but especially for
mobile devices.
The main objective is to allow the community to develop better and more
inteligent mobile games.
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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.