Evolving High-Level Imperative Program Trees with Strongly Formed Genetic Programming

We present a set of extensions to Montana's popular Strongly Typed Genetic Programming system that introduce constraints on the structure of program trees. It is demonstrated that these constraints can be used to evolve programs with a naturally imperative structure, using common high-level imperative language constructs such as loops. A set of three problems including factorial and the general even-n-parity problem are used to test the system. Experimental results are presented which show success rates and required computational effort that compare favourably against other systems on these problems, while providing support for this imperative structure