Charles University, Faculty of Mathematicsand Physics
Prague, Czech Republic
16-19 July 2007


Alessandro Antonucci, Ralph Bruehlmann, Alberto Piatti, Marco Zaffalon

Credal networks for military identification problems


Credal networks are imprecise probabilistic graphical models generalizing Bayesian networks to convex sets of probability mass functions. This makes credal networks particularly suited to capture and model expert knowledge under very general conditions, including states of qualitative and incomplete knowledge. In this paper, we present a credal network for risk evaluation in case of intrusion of civil aircrafts into a no-fly zone. The different factors relevant for this evaluation, together with an independence structure over them, are initially identified. These factors are observed by sensors, whose reliabilities can be affected by variable external factors, and even by the behavior of the intruder. A model of these observation mechanisms, and the necessary fusion scheme for the information returned by the sensors measuring the same factor, are both completely embedded into the structure of the credal network. A pool of experts, facilitated in their task by specific techniques to convert qualitative judgments into imprecise probabilistic assessments, has made possible the quantification of the network. We show the capabilities of the proposed network by means of some preliminary tests referred to simulated scenarios. Overall, we can regard this application as an useful tool to support military experts in their decision, but also as a quite general imprecise-probability paradigm for information fusion.

Keywords. Credal Networks, Information Fusion, Sensor Management, Tracking Systems.

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Authors addresses:

Alessandro Antonucci
Galleria 2
CH-6928 Manno (Lugano)

Ralph Bruehlmann
Armasuisse (W+T)
Feuerwerkerstrasse 39
CH-3600 Thun

Alberto Piatti
Via Campo Marzio 8,
CH-6500 Bellinzona

Marco Zaffalon
Galleria 2
CH-6928 Manno

E-mail addresses:

Alessandro Antonucci
Ralph Bruehlmann
Alberto Piatti
Marco Zaffalon

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