Translation of the Mutation Operator from Genetic Algorithms to Evolutionary Ontologies

Recently introduced, evolutionary ontologies rep-resent a new concept as a combination of genetic algorithms and ontologies. We have defined a new framework comprising a set of parameters required for any evolutionary algorithm, i.e. ontological space, representation of individuals, the main genetic operators such as selection, crossover, and mutation. Although a secondary operator, mutation proves its importance in creating and maintaining evolutionary ontologies diversity. Therefore, in this article, we widely debate the mutation topic in evolutionary ontologies, marking its usefulness in practice by experimental results. Also we introduce a new mutation operator, called relational mutation, concerning mutation of a relationship through its inverse.