Search Results for "e-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

The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. In contrast to other GA implementations, the library uses the concept of an evolution stream (EvolutionStream) for executing the evolution steps. Since the EvolutionStream implements the Java Stream interface, it works smoothly with the rest of the Java Stream API. ...

The NeuroSolutions: Formula Generator utility converts the weights file of a default MLP breadboard (1-hidden layer with a TanhAxon in the hidden layer and either a TanhAxon or BiasAxon in the output layer) into a usable formula that can be copied and pasted into your own programs to compute the output of the trained neural network.

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...

[Open Artificial Intelligence Library]. This library main goal is to provide a tool box to those who want to use algorithm such as neural network or genetics Algorithm and all algorithms that are commonly within the Artificial Intelligence field.

RobGP is a genetic programming system written from the ground up in C++. It's primary goals are efficiency, ease of use, and extensibility. It's distinguishing feature is that it has a modified version of Koza's architecture altering operations.

The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover

A tool that helps develope the course of cognitive thought processes through software. This tool will look at the raw hex code of any input. It establishes pattern recognition over a mesured time incrament that in itself is at a different pace.

Todbot is an AI addon to the gamestool virtual machine. The aim is to create an evolving neural network topology that should be capable of creating the optimal topology and network weighting to solve any problem given it.

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 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++.

Ocean with fishes who's are learning and evolving.

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.

A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.