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Authors: Craig Schlenoff 1 ; Sebti Foufou 2 and Stephen Balakirsky 3

Affiliations: 1 National Institute of Standards and Technology and University of Burgundy, United States ; 2 University of Burgundy and Qatar University, France ; 3 National Institute of Standards and Technology, United States

ISBN: 978-989-8565-30-3

Keyword(s): Intention Recognition, Human-Robot Interaction and Safety, State Representation, Ontology.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Human-Machine Cooperation ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Symbolic Systems

Abstract: In this paper, we present initial thoughts on an approach to ontology/logic-based intention recognition based on the recognition, representation, and ordering of states. This is different than traditional approaches to intention recognition, which use activity recognition and the ordering of activities. State recognition and representation offer numerous advantages, including the ability to infer the intention of multiple people working together and the fact that states are easier for a sensor system to recognize than actions. The focus of this work is on the domain of manufacturing assembly, with an emphasis on human/robot collaboration during the assembly process.

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Paper citation in several formats:
Schlenoff, C.; Foufou, S. and Balakirsky, S. (2012). An Approach to Ontology-based Intention Recognition using State Representations.In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012) ISBN 978-989-8565-30-3, pages 178-183. DOI: 10.5220/0004111701780183

@conference{keod12,
author={Craig Schlenoff. and Sebti Foufou. and Stephen Balakirsky.},
title={An Approach to Ontology-based Intention Recognition using State Representations},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)},
year={2012},
pages={178-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004111701780183},
isbn={978-989-8565-30-3},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)
TI - An Approach to Ontology-based Intention Recognition using State Representations
SN - 978-989-8565-30-3
AU - Schlenoff, C.
AU - Foufou, S.
AU - Balakirsky, S.
PY - 2012
SP - 178
EP - 183
DO - 10.5220/0004111701780183

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