ESKit is a portable C library that provides implementations of some self-adaptive evolution strategies. It features a simple API, comprehensive documentation, three state of the art self-adaptive evolution strategies (Isotropic CSA-ES, CMA-ES, and Separable CMA-ES), and can optionaly uses LAPACK. The implementation strictly follows the published papers introducing those evolution strategies and performs as in the published papers. A basic benchmark program is provided.
PCP (Pattern Classification Program) is a machine learning program for supervised classification of patterns. It runs in interactive and batch modes, and implements the following machine learning algorithms and methods: k-means clustering, Fisher's linear discriminant, dimension reduction using Singular Value Decomposition, Principal Component Analysis, feature subset selection, Bayes error estimation, parametric classifiers (linear and quadratic), pseudo-inverse linear discriminant, k-Nearest Neighbor method, neural networks, Support Vector Machine algorithm (SVM), model selection for SVM, cross-validation, and bagging (committee) classification.
aiParts is a set of C++ classes that can be used to implement artificial intelligence, including classes that implement the HighHope technique. Sample programs include "find the shortest path" and "assign people and/or equipment to projects". A problem assembled from subclasses of the High-Hope classes knows how to solve itself by searching for a good solution.