From the user’s point of view, setting the parameters of a genetic algorithm (GA) is far from a trivial task. Moreover, the user is typically not interested in population sizes,...
Abstract. The purpose of this paper is to test the hypothesis that simple classifiers are more robust to changing environments than complex ones. We propose a strategy for generati...
A fundamental assumption often made in supervised classification is that the problem is static, i.e. the description of the classes does not change with time. However many practi...
We show how a random mutation hill climber that does multilevel selection utilizes transposition to escape local optima on the discrete Hierarchical-If-And-Only-If (HIFF) problem....
The state of the art sees content-based filters tending towards collaborative filters, whereby email is filtered at the MTA with users feeding information back about false posit...