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An ontology model to facilitate knowledge-sharing in multi-agent systems

Published online by Cambridge University Press:  21 August 2002

VALENTINA TAMMA  and
TREVOR BENCH-CAPON
VALENTINA TAMMA
Affiliation:
Department of Computer Science, Chadwick Building, Peach Street, Liverpool, L69 7ZF, UK
TREVOR BENCH-CAPON
Affiliation:
Department of Computer Science, Chadwick Building, Peach Street, Liverpool, L69 7ZF, UK
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Abstract

This article presents and motivates an extended ontology knowledge model which represents explicitly semantic information about concepts. This knowledge model results from enriching the standard conceptual model with semantic information which precisely characterises the concept's properties and expected ambiguities, including which properties are prototypical of a concept and which are exceptional, the behaviour of properties over time and the degree of applicability of properties to subconcepts. This enriched conceptual model permits a precise characterisation of what is represented by class membership mechanisms and helps knowledge engineers to determine, in a straightforward manner, the meta-properties holding for a concept. Meta-properties are recognised to be the main tool for a formal ontological analysis that allows us to build ontologies with a clean and untangled taxonomic structure.

This enriched semantics can prove useful to describe what is known by agents in a multi-agent system, and might facilitate the use of reasoning mechanisms on the knowledge that instantiates an ontology. These mechanisms can be used to solve ambiguities that can arise when agents with heterogeneous ontologies have to interoperate in order to perform a task.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 17 , Issue 1 , March 2002 , pp. 41 - 60
Copyright
© 2002 Cambridge University Press

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Footnotes

The Ph.D. research presented in this work was funded by BT plc. We are grateful to Ray Paton for providing the medical notions necessary to model the example. We are indebted to Floriana Grasso for the stimulating discussions and the comments made throughout this Ph.D. research and, in particular, during the preparation of this article. We would also like to thank the anonymous referees for their valuable comments on an earlier version of this paper.