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Collaborative Learning of Ontology Fragments by Cooperating Agents

Collaborative Learning of Ontology Fragments by Cooperating Agents
Collaborative Learning of Ontology Fragments by Cooperating Agents
Collaborating agents require either prior agreement on the shared vocabularies that they use for communication, or some means of translating between their private ontologies. Thus, techniques that enable agents to build shared vocabularies allow them to share and learn new concepts, and are therefore beneficial when these concepts are required on multiple occasions. However, if this is not carried out in an effective manner then the performance of an agent may be adversely affected by the time required to infer over large augmented ontologies, so causing problems in time-critical scenarios such as search and rescue. In this paper, we present a new technique that enables agents to augment their ontology with carefully selected concepts into their ontology. We contextualise this generic approach in the domain of RoboCup Rescue. Specifically, we show, through empirical evaluation, that our approach saves more civilians, reduces the percentage of the city burnt, and spends the least amount of time accessing its ontology compared with other state of the art benchmark approaches.
978-0-7695-4191-4
89-96
Packer, Heather S.
0e86c31f-6460-4bbd-b6ac-c717ee2cbd96
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Packer, Heather S.
0e86c31f-6460-4bbd-b6ac-c717ee2cbd96
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Packer, Heather S., Gibbins, Nicholas and Jennings, Nicholas R. (2010) Collaborative Learning of Ontology Fragments by Cooperating Agents. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, Canada. 01 - 03 Sep 2010. pp. 89-96 .

Record type: Conference or Workshop Item (Paper)

Abstract

Collaborating agents require either prior agreement on the shared vocabularies that they use for communication, or some means of translating between their private ontologies. Thus, techniques that enable agents to build shared vocabularies allow them to share and learn new concepts, and are therefore beneficial when these concepts are required on multiple occasions. However, if this is not carried out in an effective manner then the performance of an agent may be adversely affected by the time required to infer over large augmented ontologies, so causing problems in time-critical scenarios such as search and rescue. In this paper, we present a new technique that enables agents to augment their ontology with carefully selected concepts into their ontology. We contextualise this generic approach in the domain of RoboCup Rescue. Specifically, we show, through empirical evaluation, that our approach saves more civilians, reduces the percentage of the city burnt, and spends the least amount of time accessing its ontology compared with other state of the art benchmark approaches.

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More information

Published date: 2010
Additional Information: Awarded Best Paper Event Dates: 1-3 September 2010
Venue - Dates: IEEE/WIC/ACM International Conference on Intelligent Agent Technology, Canada, 2010-09-01 - 2010-09-03
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 271241
URI: https://eprints.soton.ac.uk/id/eprint/271241
ISBN: 978-0-7695-4191-4
PURE UUID: 95fb2c32-215d-401c-ab3f-5ac535bd5d08
ORCID for Nicholas Gibbins: ORCID iD orcid.org/0000-0002-6140-9956

Catalogue record

Date deposited: 09 Jun 2010 22:58
Last modified: 13 Jun 2018 00:34

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Contributors

Author: Heather S. Packer
Author: Nicholas Gibbins ORCID iD
Author: Nicholas R. Jennings

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