An experimental study about the search mechanism in the SLAVE learning algorithm: Hill-climbing methods versus genetic algorithms

One of the basic elements in the development of the AI system is the search mechanism. The choice of the search method can determine the goodness of the developed system. In concrete, in the learning algorithms, the search mechanisms play a very important role. SLAVE is an inductive learning algorithm that describes the behavior of a system by a fuzzy rule set being a genetic algorithm of its search mechanism. In this work, we want to study the in¯uence of the search mechanism in the learning process of SLAVE. So, we analyze the results obtained with SLAVE using several search mechanisms based on hill-climbing techniques described in the literature.