The Interaction for Pilot Decision Assistance: State Machines or Learning from Story Examples?

S. Khait, N. Ardila-Torres, D. Bernard, F. Gouëzec, M. Litvova

2022

Abstract

This paper addresses some methodological aspects of the design of an adaptive interaction, in the specific context of cockpit development processes. There are many classical approaches for designing collaborative systems model user-system interaction such as synchronized state machines. On the other hand, some recent approaches are promoting alternative methods where the models are obtained by training a neural network on a set of real dialogue samples. Our benchmark study compares both approaches from an industrial perspective.

Paper Citation

in Harvard Style

Khait S., Ardila-Torres N., Bernard D., Gouëzec F. and Litvova M. (2022). The Interaction for Pilot Decision Assistance: State Machines or Learning from Story Examples?. In Proceedings of the 1st International Conference on Cognitive Aircraft Systems - Volume 1: ICCAS; ISBN 978-989-758-657-6, SciTePress, pages 61-64. DOI: 10.5220/0011958900003622

in Bibtex Style

@conference{iccas22,
author={S. Khait and N. Ardila-Torres and D. Bernard and F. Gouëzec and M. Litvova},
title={The Interaction for Pilot Decision Assistance: State Machines or Learning from Story Examples?},
booktitle={Proceedings of the 1st International Conference on Cognitive Aircraft Systems - Volume 1: ICCAS},
year={2022},
pages={61-64},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011958900003622},
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 - The Interaction for Pilot Decision Assistance: State Machines or Learning from Story Examples?
SN - 978-989-758-657-6
AU - Khait S.
AU - Ardila-Torres N.
AU - Bernard D.
AU - Gouëzec F.
AU - Litvova M.
PY - 2022
SP - 61
EP - 64
DO - 10.5220/0011958900003622
PB - SciTePress