Computational Intelligence - November 2017 - 28
Modelling Behaviour in UAV
Operations Using Higher Order
Double Chain Markov Models
©ISTOCKPHOTO.COM/FTGIPSY, ©ISTOCKPHOTO.COM/OKTAY ORTAKCIOGLU
Víctor Rodríguez-Fernández,
Antonio Gonzalez-Pardo and David Camacho
Department of Computer Science, Universidad Autónoma
de Madrid (UAM), Madrid, Spain
Digital Object Identifier 10.1109/MCI.2017.2742738
Date of publication: 12 October 2017
28
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | NOVEMBER 2017
Abstract-Creating behavioural models of human operators
engaged in supervisory control tasks with UAVs is of great
value due to the high cost of operator failures. Recent works in
the field advocate the use of Hidden Markov Models (HMMs)
and derivatives to model the operator behaviour, since they offer
interpretable patterns for a domain expert and, at the same time,
provide valuable predictions which can be used to detect
abnormal behaviour in time. However, the first order Markov
assumption in which HMMs rely, and the assumed independence
Corresponding authors:Victor Rodríguez-Fernández, David Camacho (Email: victor
.rodriguez@inv.uam.es, david.camacho@uam.es)
1556-603X/17©2017IEEE
http://www.ISTOCKPHOTO.COM/FTGIPSY
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