Zipper-based Meta-Genetic Programming

We present a zipper-based instruction set for constructing genetic programming variation operators. We study the effects of such variation operators on the lawnmower problem. Operators in this language possess the ability to outperform standard mutation and crossover in terms of both decreasing the average population error as well as the best population error. Furthermore, the expression of standard mutation and crossover in this language is trivial, allowing evolution to re-discover these operators when necessary. We conclude by using these operators in a meta-genetic programming context, showing that it is possible for zipper-based metagenetic programming to expedite evolutionary search.