Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/3480
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dc.contributor.authorMassink, Mieke-
dc.contributor.authorLatella, Diego-
dc.contributor.authorBracciali, Andrea-
dc.contributor.authorHarrison, Michael D-
dc.contributor.authorHillston, Jane-
dc.date.accessioned2013-06-09T07:30:26Z-
dc.date.available2013-06-09T07:30:26Z-
dc.date.issued2012-
dc.identifier.urihttp://hdl.handle.net/1893/3480-
dc.description.abstractPervasive environments offer an increasing number of services to a large number of people moving within these environments, including timely information about where to go and when, and contextual information about the surrounding environment. This information may be conveyed to people through public displays or direct to a person's mobile phone. People using these services interact with the system but they are also meeting other people and performing other activities as relevant opportunities arise. The design of such systems and the analysis of collective dynamic behaviour of people within them is a challenging problem. We present results on a novel usage of a scalable analysis technique in this context. We show the validity of an approach based on stochastic process-algebraic models by focussing on a representative example, i.e. emergency egress. The chosen case study has the advantage that detailed data is available from studies employing alternative analysis methods, making cross-methodology comparison possible. We also illustrate how realistic, context-dependent human behaviour, often observed in emergency egress, can naturally be embedded in the models, and how the effect of such behaviour on evacuation can be analysed in an efficient and scalable way. The proposed approach encompasses both the agent modelling viewpoint, as system behaviour emerges from specific (discrete) agent interaction, and the population viewpoint, when classes of homogeneous individuals are considered for a (continuous)approximation of overall system behaviour.en_UK
dc.language.isoen-
dc.publisherSpringer Verlag-
dc.relationMassink M, Latella D, Bracciali A, Harrison MD & Hillston J (2012) Scalable context-dependent analysis of emergency egress models, Formal Aspects of Computing, 24 (2), pp. 267-302.-
dc.rightsPublished in Formal Aspects of Computing by Springer Verlag. The original publication is available at www.springerlink.com.-
dc.subjectcollective behaviouren_UK
dc.subjectvalidationen_UK
dc.subjectstochastic process algebraen_UK
dc.subjectfluid flowen_UK
dc.subjectcontext dependencyen_UK
dc.subject.lcshLinear and multilinear algebra-
dc.subject.lcshmatrix theory-
dc.subject.lcshPartial differential equations-
dc.subject.lcshInduction (Mathematics)-
dc.titleScalable context-dependent analysis of emergency egress modelsen_UK
dc.typeJournal Articleen_UK
dc.identifier.doihttp://dx.doi.org/10.1007/s00165-011-0188-1-
dc.citation.jtitleFormal Aspects of Computing-
dc.citation.issn0934-5043-
dc.citation.volume24-
dc.citation.issue2-
dc.citation.spage267-
dc.citation.epage302-
dc.citation.publicationstatusPublished-
dc.citation.peerreviewedRefereed-
dc.type.statusPost-print (author final draft post-refereeing)-
dc.author.emailabb@cs.stir.ac.uk-
dc.contributor.affiliationIstituto di Scienza e Tecnologie dell’Informazione-
dc.contributor.affiliationIstituto di Scienza e Tecnologie dell’Informazione-
dc.contributor.affiliationComputing Science - CSM Dept-
dc.contributor.affiliationNewcastle University-
dc.contributor.affiliationUniversity of Edinburgh-
dc.identifier.isi000303537500006-
Appears in Collections:Computing Science and Mathematics Journal Articles

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