GPC++ - Genetic Programming C++ Class Library
The GP kernel is a C++ class library that can be used to apply
genetic programming techniques to all kinds of problems. An integral
component is the ability to produce automatically defined functions as
found in Koza's "Genetic Programming II". Technical documentation
(postscript format) is included. There is also a short introduction
into genetic programming.
Whats new: The documentation is also available in HTML format!
Current Version:   0.5.2
- Automatically defined functions (ADFs).
- Tournament and fitness proportionate selection.
- Demetic grouping.
- Optional steady state genetic programming kernel. Steady state
means that not a complete new population is built up every generation,
but bad performing GPs are replaced by newly evolved ones. This uses
approximately half the memory!
- Subtree crossover.
- Swap and shrink mutation.
- A way of changing every parameter of the system without
- Capacity for multiple populations (if you have the resources).
- Loading and saving of populations and genetic programs.
- Standard random number generator for complete portability. This has
been improved: population sizes of over 250000 are possible now.
- Explanations of how to write the modules for evolving code.
- A parameter study about the influence of every important
- Completely ANSI C++ compliant.
- Full and wonderful comments dispersed throughout the code.
- Internal parameter checks (can be turned off by a compiler
switch): The kernel complains if the programmer makes a mistake.
Copyright Type:   GPL
Author: Adam Fraser 1993, 1994 and Thomas Weinbrenner 1997
"gpc++0.5.2.tar.gz", compressed with gzip, 440KB.
Documentation: in gpc++0.5.2.tar.gz
Source Code Availability: Yes (full C++ sources)
Available Binary Packages: None (C++ Compiler is needed to use the software).
Targeted Platforms: C++, tested with GNU C++ Compiler 2.7.0 and C++ Compiler by SUNSoft
Software/Hardware Requirements: C++ Compiler (no exception
or template support neccessary).
Lot's of RAM and a fast computer for big and difficult problems.
home page (http://www-cs-faculty.stanford.edu/~koza)
Fraser's home page (not up to date)
Source Code Collection
Mailing Lists/USENET News Groups:
Genetic programming (comp.ai.genetic)
User Comments: Documentation format other than postscript
needed (for the operation systems written by Microsoft, ugh...). I
did it! The documentation is now available in HTML format.
Back to home page