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Aligning Experientially Grounded Ontologies Using Language Games

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Book cover Graph Structures for Knowledge Representation and Reasoning (GKR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9501))

Abstract

Ontology alignment is essential to enable communication in a multi-agent system where agents have heterogeneous ontologies. We use language games as a decentralised iterative ontology alignment solution in a multi-agent system where ontologies are grounded in measurements taken in a dynamic environment. Rather than attempting to ground ontologies through physical interaction, we design language game strategies that involve exchanging descriptions of the environment as graph patterns and interpreting descriptions using graph matching. These methods rely on structural similarity as evidence for ontology alignment. We compare various language game strategies with respect to communication overhead and alignment success and provide preliminary results which show that ontology alignment using language games that rely on descriptions alone can result in perfect alignments with only modest communication overhead. However, this requires that environmental dynamics are reasoned about when providing descriptions.

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Acknowledgments

The research reported in this paper is supported by an EPSRC Industrial CASE Award Ph.D. Studentship with Selex ES Ltd.

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Authors and Affiliations

  1. University of Edinburgh, Edinburgh, UK

    Michael Anslow & Michael Rovatsos

Authors
  1. Michael Anslow
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  2. Michael Rovatsos
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Corresponding author

Correspondence to Michael Anslow .

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Editors and Affiliations

  1. LIRMM, Montpellier Cedex 5, France

    Madalina Croitoru

  2. CRIL-CNRS, Lens, France

    Pierre Marquis

  3. Fakultät Informatik, Technische Universität Dresden, Dresden, Sachsen, Germany

    Sebastian Rudolph

  4. University of Brighton, Brighton, United Kingdom

    Gem Stapleton

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Anslow, M., Rovatsos, M. (2015). Aligning Experientially Grounded Ontologies Using Language Games. In: Croitoru, M., Marquis, P., Rudolph, S., Stapleton, G. (eds) Graph Structures for Knowledge Representation and Reasoning. GKR 2015. Lecture Notes in Computer Science(), vol 9501. Springer, Cham. https://doi.org/10.1007/978-3-319-28702-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-28702-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28701-0

  • Online ISBN: 978-3-319-28702-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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