A Genetic Programming workbench to analyze and automatically solve problems with this machine learning technique. To learn more about Genetic Algorithms and Genetic Programming in particular have a read at Wikipedia.

GP.Lab uses the ESS-GP kernel to automatically solve various problems. The list of currently implemented modules includes:

  • Mathematical function regression
  • Santa Fe Trail problem
  • RoboRail
  • Collector (temp. disabled)

The current demo is a very, very early preview but it might give you the idea.
We hope to provide regular updates and incorporate more modules in the near future!

Our YouTube channel features some short videos for various GP.Lab modules.

Any kind of feedback is welcome.


Current efforts are focussing on two areas:

  • Statistics

    The various statistic counters already gathered throughout the kernel are being collated in a new ESS-GP module and vastly extended to provide a much deeper insight into the population and the progress of the simulated evolution.
    This will include real-time graphs in GP.Lab of all relevant counters and export of any counter to GNUPLOT.
  • Refactoring the ESS-GP kernel

    The ESS-GP kernel is currently being refactored to improve adaptability for future modules and to prepare it for a generic task mechanism to support concurrent computation of statistics, population evaluation and more not bound to any particular architecture (i.e. threads, tasks, cloud, etc.).



Feel free to make a small donation if you like the program and would like to support the work on this freeware application.