  It is still unclear how an evolutionary algorithm (EA) searches a fitness
landscape, and on what fitness landscapes a particular EA will do well. The
validity of the building-block hypothesis, a major tenet of traditional genetic
algorithm theory, remains controversial despite its continued use to justify
claims about EAs. This paper outlines a research program to begin to answer
some of these open questions, by extending the work done in the royal road
project. The short-term goal is to find a simple class of functions which the
simple genetic algorithm optimizes better than other optimization methods, such
as hillclimbers. A dialectical heuristic for searching for such a class is
introduced. As an example of using the heuristic, the simple genetic algorithm
is compared with a set of hillclimbers on a simple subset of the
hyperplane-defined functions, the pothole functions.
