genetic programming, machine learning This paper describes the results of using genetic programming with bounded iteration constructs, which allow the computational complexity of the solution to be an emergent property. It is shown that such operators render the even-6-parity problem trivial, and the results of experiments with other, harder, problems that require 0(n) complexity are shown. This method is contrasted with Automatically Defined Iterators. Abstract This paper describes the results of using genetic programming with bounded iteration constructs, which allow the computational complexity of the solution to be an emergent property. It is shown that such operators render the even-6-parity problem trivial, and the results of experiments with other, harder, problems that require O(n) complexity are shown. This method is contrasted with Automatically Defined Iterators.