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Genetic programming framework / library search

I am looking for a framework or library that could work with genetic programming (koza style) not only with mathematical functions, but also with loops, variables or constant assignments, object creation or function calls. I am not sure if such a branch of genetic algorithms exists, and if it has a name. I did my best to find information, although there is little information on the Internet about this particular topic.

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HeuristicLab has a powerful implementation of Genetic Programming. It includes issues such as Symbolic Regression, Symbolic Classification, Time Series, Santa Fe Ant Trail, and there is a tutorial for implementing custom problems such as a lawn mower (which is similar to Santa Fe Ant Trail). HeuristicLab is implemented in C # and runs on Windows. It is released under the GPL and is free to download .

The GP implementation is very flexible and extensible, but also optimized for performance using online computing to avoid array allocation and memory overhead. We include several reference problem situations for symbolic regression and classification. There are also more algorithms available, such as Random Forests, Neural Networks, k-NN, SVM (if you are doing a regression or classification).

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If you are not talking about GP toolbars in MATLAB, for example: http://gplab.sourceforge.net/ ...

you can try:

Among them: JGAP and ECJ are quite popular.

Take a look at this link: http://www.tc33.org/genetic-programming/genetic-programming-software-comparison/ ... this provides a good comparison between all the frameworks.

Hope this helps.

Greetings.

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Source: https://habr.com/ru/post/1491178/

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