Contextual merging of uncertain information for better informed plan selection in BDI systems

Sarah Calderwood, Kevin McAreavey, Weiru Liu, Jun Hong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sensor information (e.g. temperature, voltage, etc.) obtained from heterogeneous sources in SCADA systems may be uncertain and incomplete, while sensors may be unreliable or conflicting. To address these issues we apply Dempster-Shafer (DS) theory to correctly model the information so that it can be merged in a consistent way. Unfortunately, existing merging operators are not suitable for every situation. We adapt a context-dependent strategy from possibility theory where we determine the context for when to merge using Dempster's rule of combination (i.e. for low conflicting information) and then resort to Dubois and Prade's disjunctive rule to merge information which is highly conflicting. We demonstrate the suitability of our approach with a scenario of a smart grid SCADA system modelled using the Belief-Desire-Intention (BDI) multi-agent framework. In particular, we use the notion of epistemic states to model combined uncertain sensor information for better informed selection of predefined plans.
Original languageEnglish
Title of host publicationProceedings of the 2015 World Congress on Industrial Control Systems Security (WCICSS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages64-65
Number of pages2
ISBN (Print)978-1-908320-58
DOIs
Publication statusPublished - 29 Feb 2016
Event2015 World Congress on Industrial Control Systems Security (WCICSS) - London, United Kingdom
Duration: 14 Dec 201514 Dec 2016
http://www.wcicss.org/

Conference

Conference2015 World Congress on Industrial Control Systems Security (WCICSS)
CountryUnited Kingdom
CityLondon
Period14/12/201514/12/2016
Internet address

Fingerprint

Merging
SCADA systems
Sensors
Electric potential
Temperature

Cite this

Calderwood, S., McAreavey, K., Liu, W., & Hong, J. (2016). Contextual merging of uncertain information for better informed plan selection in BDI systems. In Proceedings of the 2015 World Congress on Industrial Control Systems Security (WCICSS) (pp. 64-65). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/WCICSS.2015.7420326
Calderwood, Sarah ; McAreavey, Kevin ; Liu, Weiru ; Hong, Jun. / Contextual merging of uncertain information for better informed plan selection in BDI systems. Proceedings of the 2015 World Congress on Industrial Control Systems Security (WCICSS). Institute of Electrical and Electronics Engineers (IEEE), 2016. pp. 64-65
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Calderwood, S, McAreavey, K, Liu, W & Hong, J 2016, Contextual merging of uncertain information for better informed plan selection in BDI systems. in Proceedings of the 2015 World Congress on Industrial Control Systems Security (WCICSS). Institute of Electrical and Electronics Engineers (IEEE), pp. 64-65, 2015 World Congress on Industrial Control Systems Security (WCICSS), London, United Kingdom, 14/12/2015. https://doi.org/10.1109/WCICSS.2015.7420326

Contextual merging of uncertain information for better informed plan selection in BDI systems. / Calderwood, Sarah; McAreavey, Kevin; Liu, Weiru; Hong, Jun.

Proceedings of the 2015 World Congress on Industrial Control Systems Security (WCICSS). Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 64-65.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Calderwood S, McAreavey K, Liu W, Hong J. Contextual merging of uncertain information for better informed plan selection in BDI systems. In Proceedings of the 2015 World Congress on Industrial Control Systems Security (WCICSS). Institute of Electrical and Electronics Engineers (IEEE). 2016. p. 64-65 https://doi.org/10.1109/WCICSS.2015.7420326