If you are sure you want to do this, you want genetic programming, rather than a genetic algorithm. GP allows you to evolve tree-structured programs. What you would do would be to give it a bunch of primitive operations (while($register), read($register), increment($register), decrement($register), divide($result $numerator $denominator), print, progn2 (this is GP speak for “execute two … Read more
Genetic algorithms (GA) are search algorithms that mimic the process of natural evolution, where each individual is a candidate solution: individuals are generally “raw data” (in whatever encoding format has been defined). Genetic programming (GP) is considered a special case of GA, where each individual is a computer program (not just “raw data”). GP explore … Read more
There is some debate as to whether Roger’s Mona Lisa program is Genetic Programming at all. It seems to be closer to a (1 + 1) Evolution Strategy. Both techniques are examples of the broader field of Evolutionary Computation, which also includes Genetic Algorithms. Genetic Programming (GP) is the process of evolving computer programs (usually … Read more
This is something I have been considering in my own research, and I’d say there are many reasons: The vast majority of research in the GP field has focused on producing formulas rather than the sort of software that gets produced by most programmers. There are plenty of computer scientists in the field, but very … Read more
After developing my own Genetic Programming didactic application, I found a complete Genetic Programming Framework called AForge.NET Genetics. It’s a part of the Aforge.NET library. It’s licensed under LGPL.