Abstract

Worst case complexity analyses of algorithms are sometimes held to be less informative about the real difficulty of computation than are expected complexity analyses. We show that the two most common representations of problem solving in cognitive science each admit aigorithms that have constant expected complexity, and for one of these representations we obtain constant expected complexity bounds under a variety of probability measures.