Aligning Experientially Grounded Ontologies using Language Games

Michael Anslow, Michael Rovatsos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 and that partial matching of descriptions is used when there are inconsistencies between descriptions and local knowledge.
Original languageEnglish
Title of host publicationGraph Structures for Knowledge Representation and Reasoning
Subtitle of host publication4th International Workshop, GKR 2015, Buenos Aires, Argentina, July 25, 2015, Revised Selected Papers
PublisherSpringer International Publishing
Pages15-31
Number of pages17
ISBN (Electronic)978-3-319-28702-7
ISBN (Print)978-3-319-28701-0
DOIs
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
Volume9501
ISSN (Print)0302-9743

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