Bench-Capon, Trevor

Euzenat, Jerome

Laera, Loredana

Payne, Terry R.

Tamma, Valentina

English

Southampton (e-Prints Soton)

Agents Arguing Over Ontology AlignmentsLoredana Laera a Valentina Tamma a J´ erˆ ome Euzenat bTrevor Bench-Capon a Terry Payne ca Department of Computer Science, University of Liverpool,UKb INRIA Rhˆ one-Alpes, Montbonnot, Francec Department of Electronics and Computer Science, University of Southampton,UK1 Extended AbstractOntologies play an important role in inter-agent communication, by providing the deﬁnitions ofthe vocabularies used by agents to describe the world [4]. An agent can use such a vocabulary toexpress its beliefs and actions, and so communicate about them. Ontologies contribute to semanticinteroperability when agents are embedded in open, dynamic environments, such as the Web andits proposed extension, the Semantic Web [2]. However, in this type of environment there cannotbe a single universally shared ontology that is agreed upon by all the parties involved, as this wouldresult in imposing a standard communication vocabulary. Instead, every agent will typically use itsown private ontology, which may not be understandable by other agents. Interoperability thereforerelies on the ability to reconcile di erent existing ontologies that may be heterogeneous in formatand with partially overlapping domains [7]. This reconciliation usually relies on the existence ofcorrespondences (or mappings) between agent ontologies, and using them in order to interpret ortranslate messages exchanged by agents. The underlying problem is usually termed an ontologymatching problem [3]. Many matching algorithms that are able to produce such alignments havebeen proposed [6]. The availability of a dedicated agent, here termed as an Ontology AlignmentService, that is able to provide such correspondences between two ontologies is only the beginning ofa solution to achieving interoperability between agents, as any given candidate set of alignments isonly suitable in certain contexts. For a given context, agents might have di erent and inconsistentperspectives; i.e. interests and preferences, on the acceptability of a candidate mapping, each ofwhich may be rationally acceptable. This may be due to the subjective nature of ontologies, tothe context and the requirement of the alignments and so on. For example, an agent may beinterested in accepting only those mappings that have linguistic similarities, since its ontologyis too structurally simple to realise any other type of mismatch. Moreover, any decision on theacceptability of these mappings has to be made dynamically (at run time), due to the fact that theagents have no prior knowledge of either the existence or constraints of other agents.In order to address this problem, we present a framework to support agents to negotiateagreement on the terminology they use in order to communicate, by allowing them to expresstheir preferred choices over candidate correspondences. Agreements are determined by means ofargument-based negotiation to deal speciﬁcally with arguments that support or oppose the proposedcorrespondences between ontologies. Our argumentation framework is based on the Value-basedArgument Frameworks (V AFs) of [1]. It prescribes di erent strengths to arguments on the basisof the values they promote and the ranking given to these values by the audience for the argu-ment. This allows us to systematically relate strengths of arguments to their motivations, and toaccommodate di erent audiences with di erent interests and preferences. Thus, the preferences willrepresent the motivations of the agents to determine whether a mapping is accepted or rejected.The set of potential arguments are clearly identiﬁed and grounded on the underlying ontology lan-guage, the standard OWL1, and the kinds of mapping that can be supported by any such argument1http://www.w3.org/OWL/are clearly speciﬁed. The reasons justifying the correspondences are classiﬁed in several di erenttypes, which correspond to the type of categorizations underlying ontology matching algorithms [7].Such a classiﬁcation will also coincide with the types of values in the V AF. Therefore, for example,an audience may specify that terminological arguments are preferred to semantic arguments, orvice versa. This may vary according to the nature of the ontologies being aligned. For example,semantic arguments will be given more weight in a fully axiomatised ontology, compared to thatin a lightweight ontology where there is very little reliable semantic information on which to basesuch arguments. Therefore, in V AFs, arguments against or in favour of a candidate mapping areseen as grounded on their type. In this way, we are able to motivate the choice between preferredextensions by reference to the type ordering of the audience concerned.Given a set of arguments justifying mappings organised into a valued-based argumentationframework, an agent will be able to determine which mappings are acceptable by computing thepreferred extensions with respect to its preferences. Since, in our framework, an audience may havemultiple preferred extensions, we thus deﬁne an agreed alignment and an agreeable alignment. Anagreed alignment has been deﬁned as the set of correspondences supported by those argumentswhich are in every preferred extension of every agent. An agreeable alignment extends the agreedalignment with those correspondences supported by arguments which are in some preferred exten-sion of every agent. Whilst the mappings included in the agreed alignments can be consideredvalid and consensual for all agents, the agreeable alignments have a uncertain background, due tothe di erent alternative positions that each agent can take. However, given our context of agentcommunication, we seek to accept as many candidate mappings as possible. We will therefore takeinto consideration both sets of alignments - agreed and agreeable. The dialogue between agentsconsists simply of the exchange of individual argumentation frameworks, from which they can in-dividually compute acceptable mappings. Therefore, this work provides a concrete instantiationof the meaning negotiation process that we would like agents to achieve. Moreover, in contrast tocurrent ontology matching procedures, the choice of alignment is based on two clearly identiﬁedelements: (i) the argumentation framework, which is common to all agents, and (ii) the preferencerelations which are private to each agent. We believe that this approach will achieve more soundand e ective mutual understanding and communication in agents system.Future work includes the use of a negotiation process to enable agents to reach an agreementon a mapping when they di er in their ordering of argument types. Another interesting topic forfuture work would be to investigate how to argue about the whole alignment, and not only theindividual candidate mappings. These arguments could occur when a global similarity measurebetween the whole ontologies is applied.More details can be found in an extended version of this paper [5].References[1] T. Bench-Capon. Persuasion in Practical Argument Using Value-Based Argumentation Frame-works. In Journal of Logic and Computation, volume 13, pages 429–448, 2003.[2] T. Berners-Lee, J. Hendler, and O. Lassila. The Semantic Web. Scientiﬁc American, 284(5):34–43, 2001.[3] J. Euzenat and P. Valtchev. Similarity-based ontology alignment in OWL-Lite. In Proceedingsof the European Conference on Artiﬁcial Intelligence (ECAI 2006), 2004.[4] T. R. Gruber. A Translation Approach to Portable Ontology Speciﬁcations. Knowledge Acqui-sition, 5(2):199–220, 1993.[5] L. Laera, V. Tamma, J. Euzenat, and Terry R. Payne T. Bench-Capon. Reaching agreementover ontology alignments. In International Semantic Web Conference 2006, pages 371–384,2006.[6] P. Shvaiko and J. Euzenat. A survey of schema-based matching approaches. Journal on datasemantics, 4:146–171, 2005.[7] P.R.S. Visser, D.M. Jones, T.J.M. Bench-Capon, and M.J.R. Shave. Assessing Heterogeneityby Classifying Ontology Mismatches. In N. Guarino, editor, Proceedings of the FOIS’98, 1998.

Agents Arguing Over Ontology Alignments

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