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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.
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.
This is an implementation of Donald Knuth's Algorithm X ("dancing links"). This is primarily a sudoku generator and solver, though it can be used to solve other exact cover problems.
Picsart Enterprise Background Removal API for Stunning eCommerce Visuals
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With our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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.
Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.
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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.
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.
The simpliZia-program implements the simplex-algorithm and is designed to help students of Operations Research to understand and learn the algorithm. This is a german project, source and program are actually written in german.
Project Tokaf is an general implementation of top-k algorithm. It provides interfaces for all modules that are needed. It also features user preferences module, for computing new preferences and manipulating existing ones.
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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 intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.
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.