Symbolic AI for Crew Assistance: Using Ontologies in the Cockpit

Dargent Lauren, Girod Hervé

2022

Abstract

This paper presents the use of knowledge-based technologies, ontologies, as an interesting way to create a reasoning framework for the machine. Dassault Aviation is convinced that, for system automation, this technique is complementary with data-driven approaches and enhances performances: while deep learning algorithms and other machine learning techniques can provide “sensory services”, such as understanding aural messages, understanding images, texts, interpreting low-level signals, etc., knowledge-based technologies can provide the system a framework to ensure “cognitive services”, such as manipulating concepts and reasoning. From Dassault Aviation’s perspective, both approaches are necessary to team the system and the crew in tomorrow’s missions.

Paper Citation

in Harvard Style

Lauren D. and Hervé G. (2022). Symbolic AI for Crew Assistance: Using Ontologies in the Cockpit. In Proceedings of the 1st International Conference on Cognitive Aircraft Systems - Volume 1: ICCAS; ISBN 978-989-758-657-6, SciTePress, pages 88-91. DOI: 10.5220/0011964000003622

in Bibtex Style

@conference{iccas22,
author={Dargent Lauren and Girod Hervé},
title={Symbolic AI for Crew Assistance: Using Ontologies in the Cockpit},
booktitle={Proceedings of the 1st International Conference on Cognitive Aircraft Systems - Volume 1: ICCAS},
year={2022},
pages={88-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011964000003622},
isbn={978-989-758-657-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Cognitive Aircraft Systems - Volume 1: ICCAS
TI - Symbolic AI for Crew Assistance: Using Ontologies in the Cockpit
SN - 978-989-758-657-6
AU - Lauren D.
AU - Hervé G.
PY - 2022
SP - 88
EP - 91
DO - 10.5220/0011964000003622
PB - SciTePress