The control of genetic algorithms using version spaces

Abstract

It is demonstrated how the traditional genetic algorithm (GA) can be augmented by incorporating domain knowledge in the form of a version space (VS) into the structure. This hybrid inductive learning system is designed to handle problems in concept learning using the VS to control the search process that is performed by the GA. In this hybrid system a novel class of schemata is present called the hyperschema. A theorem for the hyperschema analogous to that for the traditional schema is presented. This theorem demonstrates how the addition of domain knowledge in the form of a VS allows the hybrid system to exploit schemata of higher order and defining length via a hitchhiking effect. >