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On Observability Analysis in Multiagent Systems
Mu, Chunyan; PANG, Jun
2023In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI'23)
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Abstract :
[en] In multiagent systems (MASs), agents’ observation upon system behaviours may improve the overall team performance, but may also leak sensitive information to an observer. A quantified observability analysis can thus be useful to assist decision-making in MASs by operators seeking to optimise the relationship between performance effectiveness and information exposure through observations in practice. This paper presents a novel approach to quantitatively analysing the observability properties in MASs. The concept of opacity is applied to formally express the characterisation of observability in MASs modelled as partially observable multiagent systems. We propose a temporal logic oPATL to reason about agents’ observability with quantitative goals, which capture the probability of information transparency of system behaviours to an observer, and develop verification techniques for quantitatively analysing such properties. We implement the approach as an extension of the PRISM model checker, and illustrate its applicability via several examples.
Disciplines :
Computer science
Author, co-author :
Mu, Chunyan;  Department of Computing Science, University of Aberdeen
PANG, Jun  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
External co-authors :
yes
Language :
English
Title :
On Observability Analysis in Multiagent Systems
Publication date :
September 2023
Event name :
26th European Conference on Artificial Intelligence
Event date :
2023
Audience :
International
Main work title :
Proceedings of the 26th European Conference on Artificial Intelligence (ECAI'23)
Publisher :
IOS Press
ISBN/EAN :
978-1-64368-437-6
978-1-64368-436-9
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 19 October 2023

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