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Bayesian network for the prediction of situation awareness errors

Jean Marc Salotti 1, 2, 3, 4
1 COGNITIQUE
IMS - Laboratoire de l'intégration, du matériau au système
2 AUCTUS - Augmenting human comfort in the factory using cobots
Inria Bordeaux - Sud-Ouest, Bordeaux INP - Institut Polytechnique de Bordeaux
Abstract : A new method is proposed to predict situation awareness errors in training simulations. It is based on Endsley's model and the eight 'situation awareness demons' that she described. The predictions are determined thanks to a Bayesian network and noisy-or nodes. A maturity model is introduced to come up with the initialisation problem. The NASA behavioural competency model is also used to take individual differences into account.
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https://hal.inria.fr/hal-01944420
Contributor : Jean-Marc Salotti Connect in order to contact the contributor
Submitted on : Wednesday, December 5, 2018 - 11:46:14 AM
Last modification on : Tuesday, February 9, 2021 - 4:14:06 PM
Long-term archiving on: : Wednesday, March 6, 2019 - 12:45:56 PM

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Jean Marc Salotti. Bayesian network for the prediction of situation awareness errors. International Journal of Human Factors Modelling and Simulation, Inderscience, 2018, 6 (2/3), pp.119-126. ⟨10.1504/IJHFMS.2018.093174⟩. ⟨hal-01944420⟩

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