Agent Clustering based on Semantic Negotiation

Forming groups of agents is an important task in many agent-based applications, for example whendetermining a coalition of buyers in an e-commerce community or organizing differentWeb servicesin a Web services’ composition. A key issue in this context is that of generating groups of agentssuch that the communication among agents of the same group is not subjected to comprehensionproblems. To this purpose, several approaches have been proposed in the past in order to formgroups of agents based on some similarity measures among agents. Such similarity measuresare mainly based on lexical and/or structural similarities among agent ontologies. However, thenecessity of taking into account a semantic component of the similarity value arises, for exampleby considering the context in which a term is used in an agent ontology. Therefore we propose aclustering technique based on the HISENE semantic negotiation protocol, using a similarity valuethat has lexical, structural and semantic components. Moreover,we introduce a suitable multiagentarchitecture that allows computing agent similarities by means of an efficient distributed approach.