Generally, we use GP to make optimizations in exponentially sized search spaces. Lets say you're searching in a 60-dimensional space. If every dimension you a

Generally, we use GP to make optimizations in exponentially sized search spaces. Lets say you're searching in a 60-dimensional space. If every dimension you add doubles your space, 10 years of Moore's law gets you a ~65-dimensional space. It's useful to keep in mind that given an entire universe's worth of entropy and a few billion years, the best (apparently) nature could come up with is us. That said, I do have a few fun ideas: 1. Evolve a simple natural langague date parsing library (e.g. GNU getdate, but smarter and able to handle noise) over an approximate regex library like agrep. Can you create a regex equivalent to an autoencoder? 2. Create a database of abstract syntax tree chunks from every OSS project you can find on the web. Try to learn a system that would dump chunks of code into your IDE when you hit a hot key. For example, you could write a method that takes an integer argument, and perhaps it would insert a for loop counting to n. A more intelligent system could take into account instance variables, available methods, etc. Think of it as an extension of statistical natural language methods; like SCIgen (the fake CS paper generator).