The aim of libgpr is to make using Genetic Programming easy to include within any C/C++ application. Genetic programming (GP) is a powerful technique, inspired by the process of natural selection, which can be utilized to automatically discover programs which produce a desired input to output transformation. The problem can be stated simply as:

"Given some behavior find a program which produces this behavior, or a close approximation of it"

Both classical tree-based and Cartesian forms of Genetic Programming are supported, including self-modifying CGP. It's also possible to export the results in the form of C programs suitable for running on Arduino micro-controllers. Provided that the simulation system used to evaluate fitness is somewhat similar to a real hardware implementation then you should be able to upload the program to an Arduino, plug in some inputs and outputs and obtain similar types of behavior.

Installation

To build from source:

    sudo apt-get install gnuplot libz-dev
    make
    sudo make install

This creates the library and installs it into /usr/local. If you need to run the unit tests after installing as above:

    make tests
    ./libgpr_tests

Or to check for any memory leaks:

    valgrind --leak-check=full ./libgpr_tests

There are also some example programs within the libtest and libtest_cartesian directories, which can be built by running:

    make ltest
    ./libgpr

or

    make ltestc
    ./libgpr

Usage

For more detailed information on usage see http://robotics.uk.to/doku.php?id=libgpr or view the manpage.

References

For more information on the Genetic Programming method, see:

* Genetic Programming: On the programming of computers by means of natural selection, John R. Koza, MIT Press

* https://en.wikipedia.org/wiki/Genetic_programming

* http://www.cartesiangp.co.uk

* https://en.wikipedia.org/wiki/Arduino

* Self-Modifying Cartesian Genetic Programming, Simon Harding

* Automatic Algorithm Invention with a GPU  https://www.youtube.com/watch?v=xQDazGrKsuM