For about a year I have been thinking about writing a program that writes programs. This would primarily be a playful exercise that might teach me some new concepts. My inspiration came from negentropy and the ability for order to emerge from chaos and new chaos to arise out of order in infinite succession.
To be more specific, the program would start by writing a short random string. If the string compiles the programs will log it for later comparison. If the string does not compile the program will try to rewrite it until it does compile. As more strings (mini ‘useless’ programs) are logged they can be parsed for similarities and used to generate a grammar. This grammar can then be drawn on to write more strings that have a higher probability of compilation than purely random strings.
This is obviously more than a little silly, but I thought it would be fun to try and grow a program like this. And as a byproduct I get a bunch of unique programs that I can visualize and call art.
I’ll probably write this in Ruby due to its simple syntax and dynamic compilation and then I will visualize in processing using ruby-processing.
What I would like to know is:
- Is there a name for this type of programming?
- What currently exists in this field?
- Who are the primary contributors?
- BONUS! – In what ways can I procedurally assign value to output programs beyond compiles(y/n)?
I may want to extend the functionality of this program to generate a program based on parameters, but I want the program to define those parameters through running the programs that compile and assigning meaning to the programs output. This question is probably more involved than reasonable for a bonus, but if you can think of a simple way to get something like this done in less than 23 lines or one hyperlink, please toss it into your response.
I know that this is not quite meta-programming and from the little I know of AI and generative algorithms they are usually more goal oriented than what I am thinking. What would be optimal is a program that continually rewrites and improves itself so I don’t have to ^_^
Look up “genetic programming.”
Edit to respond to comments:
@chris, @Kasturi: true. What was described in the OP is a system for inferring a grammar by brute-force attempts to make some concrete syntax compile, and then back-generating new concrete syntax from the grammar. If you’re bound to have something very closely matching that description… the best advice I have is to look into building a hidden Markov model from concrete syntax in some language with very minimal syntax. I’d consider using a minimal combinatorial logic (something akin in spirit to the Unlambda language).
On the other hand, genetic programming is a technique with some developed practice and literature, and is not “deterministic” but rather a stochastic process. It’s also a pretty broad term—arguably the system of the OP is a limiting case of GP with 0% crossover and 100% mutation.