RGP is a simple yet flexible Genetic Programming system for the R environment. The system implements classical untyped tree-based genetic programming as well as more advanced variants including, for example, strongly typed genetic programming and Pareto genetic programming.
The RGP Wiki contains a short tutorial on Getting Started. A version of the tutorial fitting your locally installed RGP version is always available by typing
vignette("rgp_introduction") at the R prompt.
In addition, the RGP Wiki contains documentation, information on how to access the code repository, and on how to contribute.
Please use the Forum for discussing questions regarding RGP.
Also see the News section of the site for recent developments.
- Subprojects: RGP User Interface
Manager: Olaf Mersmann, Oliver Flasch
Developer: Jörg Stork, Krzysztof Krawiec, Noah Ispas, Tobias Brandt
Reporter: Ahmed Nagi, Alison Weber, Johannes Ranke, Jongseong Kim, Jörg Stork, Krzysztof Krawiec, Noah Ispas, Rahul Savani, Renata Camargo, Tobias Brandt, vinicius melo
New Book on Optimization with R(GP)
Paulo Cortez's new book "Modern Optimization with R" contains practical examples on the successful application of RGP.
RGP 0.4-1 released on CRAN
RGP version 0.4-1 is a maintenance release recommended for all RGP users.
The RGP tutorial "Getting Started" has been updated for RGP 0.4-0.
RGP 0.4-0 released on CRAN
RGP 0.4-0 brings a much improved Pareto-GP search strategy for symbolic regression and support for a modern web-based user interface.
RGP version 0.3-4 released on CRAN
RGP version 0.3-4 contains bugfixes and performance improvements.