Reaching Semantic Agreements through Interaction Manuel Atencia Marco Schorlemmer (IIIA-CSIC, Artificial Intelligence Research Institute, Spain {manu,marco}@iiia.csic.es) Abstract: We address the complex problem of semantic heterogeneity in multiagent communication by looking at semantics related to interaction. Our approach takes the state of the interaction in which agents are engaged as the basis on which the semantic alignment rests. In this paper we describe an implementation of this technique and provide experimental results on interactions of varying complexity. Key Words: interaction model, alignment protocol, alignment mechanism Category: I.2.11, I.2.12 1 Introduction We tackle the problem of semantic heterogeneity as it arises when combining separately engineered software entities in open and distributed environments. In particular, we focus on how to reach mutual understanding of the terminology that occurs in communicated messages during a multiagent interaction. Semantic heterogeneity is most commonly addressed either by having recourse to shared ontologies, or else by resolving terminological mismatches by ontology mapping [Kalfoglou and Schorlemmer 2003, Euzenat and Shvaiko 2007]. Ontologies may indeed be very useful for stable domains and closed communities, but the cost of guaranteeing global semantics increases quickly as the number of participants grows. Ontology mapping allows for more dynamism and openness, but current techniques compute semantic similarity in an interaction-independent fashion, for instance, by exploring the taxonomic structure of ontologies or by resorting to external sources such as WordNet, where semantic relations like synonymy, among others, were determined prior to interaction and independently from it. Hence, in general, these techniques do not address the fact that the meaning of a term is also relative to its use in the context of an interaction. In this paper we aim at proving that this more pragmatic context may guide interacting agents in reaching a mutual understanding of their respective local terminologies. For this we make an empirical evaluation of an implementation of the Interaction-Situated Semantic Alignment (I-SSA) technique (Section 2), originally formalised in [Atencia and Schorlemmer 2008]. Our implementation of I-SSA lets two agents interact through communicative acts according to two separate interaction models locally managed by each agent. All terminological mismatches during communication are handled at a meta-level in the context of an alignment protocol. As interaction-modelling formalism we have initially Proceedings of I-KNOW ’09 and I-SEMANTICS ’09 2-4 September 2009, Graz, Austria 726