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A concise example of the classical genetic algorithm, with a fancy windows terminal display. Features DNA editing, save/load, customizable constraints and statistics logging.
NeuroDraughts is a Draughts/Checkers game that teaches itself how to play through self play. It combines an Artificial Neural Network, trained by Temporal Difference Learning using some Genetic Algorithm style behaviour.
Garbage collection for C++. Small portable library that can even be multithreaded (with some restrictions). It uses the mark & sweep algorithm. No dependencies. Provides garbage-collected array class; provides wrapper class for external classes.
MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.
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The "Framework for Implicit Graph Algorithms and Representations by OBDDs" (Figaro) automatically manages experiments with input generator and algorithm plugins. It already contains some generators and algorithms for graph and scheduling problems.
Common utility methods, classes and algorithm library for general use. Although this library focuses on common utility algorithms, main goal of this library is ease of use by trading some flexibility.
Algorithm that can generate any given series of probabilities G, using only fair coins.
The algorithm creates a Huffman tree by decomposing any probability P into a sum of probabilites Q, where each Q is a power of 1/2.
Than using the coins, the tra
CRefDynGenStrArray is a fast and space efficient STL-vector(char)-based dynamic array of generic strings. Supports storing and retrieval of Pascal&C style strings, STL strings and vector(char). Provides STL algorithm adapter class.
ABKit is a C++ library intended to accelerate board games development by providing the thinking engine under the Alpha-Beta algorithm.
The application just need to create a few C++ methods to adapt to the actual game (like Chess, Checkers, ...).
ga2 is a simple C++ library providing the necessary base classes to implement a genetic algorithm in C++. It is based loosely on Goldberg's canonical GA, but with many modifications, improvements and additional features. Essentially feature-complete, and
The Algorithm Load Analyzer enables developers to test algorithms for resource usage analysis. The algolyzer library provides real-time monitoring and implementation-level recording of system resource loads during the execution of custom routine(s).
Integer Singular Value Decomposition Genetic Algorithm Function Fitter. This is an optimization algorithm that performs a similar role to a neural network.
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.
The SBMLevolver is an evolutionary algorithm package that creates SBML models with user-specified properties and behaviour from a given set of building blocks. Applications lie in network reconstruction and synthetic biology.
Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.