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[WSS19] Evolving randomly generated programs

Posted 6 years ago
POSTED BY: Carlos Muñoz
3 Replies

Excellent. Just what I had in mind with this Community post and this related blog post.

As Carlos points out, the fitness function Range[x] is just for demonstration purposes. As i wrote in my post:

The initial exercise described above is about the mechanics of the process rather that the outcome. The second stage is much more challenging, as the goal is to develop new functionality, rather than simply to replicate what already exists. It would entail defining a much more complex objective function, as well as perhaps some constraints on program size, the number and types of WL objects used, etc. An interesting exercise, for example, would be to try to develop a metaprogramming system capable of winning the Wolfram One-Liner contest. Here, one might characterize the objective function as “something interesting and surprising”, and we would impose a tight constraint on the length of programs generated by the metaprogramming system to a single line of code. What is “interesting and surprising”? To be defined – that’s a central part of the challenge. But, in principle, I suppose one might try to train a neural network to classify whether or not a result is “interesting” based on the results of prior one-liner competitions.

All-in-all a great start by Carlos, which hopefully will open up the field to others, now that there is a clear path to follow.

POSTED BY: Jonathan Kinlay

I was asked about my code so I wanted to mention something for anyone interested in revising or using my code. Most of the code is somewhat ordered and cleaned up, but there is a lot of file ordering, selection and removing some pieces that are not very important that I have to do. It will take me a few days as I am travelling, so I get some time I will make the code more readable and specify how and why I did it like that. Also, this is my first attempt in using genetic programs, so some parts may not be as efficient as they could be. For more complex fitness functions, using more generations or a larger population you might have to do some rewriting of the code. If you do something with the code and want to share let me know :).

POSTED BY: Carlos Muñoz

Thanks a lot for the feedback! I like your blog post about metaprogramming and will look more into it.

POSTED BY: Carlos Muñoz
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