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Authors: Sarah Calderwood ; Kevin McAreavey ; Weiru Liu and Jun Hong

Affiliation: Queen's University Belfast, United Kingdom

Keyword(s): Dempster-Shafer Theory, Event Detection, Event Inference, Uncertain Event-observations.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Representation and Reasoning ; Symbolic Systems ; Uncertainty in AI

Abstract: This paper presents an event modelling and reasoning framework where event-observations obtained from heterogeneous sources may be uncertain or incomplete, while sensors may be unreliable or in conflict. To address these issues we apply Dempster-Shafer (DS) theory to correctly model the event-observations so that they can be combined in a consistent way. Unfortunately, existing frameworks do not specify which event-observations should be selected to combine. Our framework provides a rule-based approach to ensure combination occurs on event-observations from multiple sources corresponding to the same event of an individual subject. In addition, our framework provides an inference rule set to infer higher level inferred events by reasoning over the uncertain event-observations as epistemic states using a formal language. Finally, we illustrate the usefulness of the framework using a sensor-based surveillance scenario.

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Paper citation in several formats:
Calderwood, S.; McAreavey, K.; Liu, W. and Hong, J. (2017). Modelling and Reasoning with Uncertain Event-observations for Event Inference. In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-220-2; ISSN 2184-433X, SciTePress, pages 308-317. DOI: 10.5220/0006254103080317

@conference{icaart17,
author={Sarah Calderwood. and Kevin McAreavey. and Weiru Liu. and Jun Hong.},
title={Modelling and Reasoning with Uncertain Event-observations for Event Inference},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2017},
pages={308-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006254103080317},
isbn={978-989-758-220-2},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Modelling and Reasoning with Uncertain Event-observations for Event Inference
SN - 978-989-758-220-2
IS - 2184-433X
AU - Calderwood, S.
AU - McAreavey, K.
AU - Liu, W.
AU - Hong, J.
PY - 2017
SP - 308
EP - 317
DO - 10.5220/0006254103080317
PB - SciTePress

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