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JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included.
hcxselect is a small and fast CSS selector engine for C++. It parses CSS selector expressions and applies them to a set of document nodes (or a whole tree) parsed via htmlcxx, a simple non-validating HTML parser. Thus, it allows you to use CSS selectors in your C++ program without much bloat.
Command-line/Ant-task/embeddable text file preprocessor. Macros, flow control, expressions. Recursive directory processing. Extensible in Java to display data from any data sources (as database). Can generate complete homepages (tree of HTML-s, images, etc.
pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.
Parser for mathematical expressions written in Java. Expressions may contain variables, functions and constants. The parser turns a string argument into an expression tree, which then can be evaluated.
This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.