Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/3555
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Authors: Massink, Mieke
Latella, Diego
Bracciali, Andrea
Hillston, Jane
Contact Email: abb@cs.stir.ac.uk
Title: Modelling Non-linear Crowd Dynamics in Bio-PEPA
Editors: Giannakopoulou, D
Orejas, F
Citation: Massink M, Latella D, Bracciali A & Hillston J (2011) Modelling Non-linear Crowd Dynamics in Bio-PEPA In: Giannakopoulou D, Orejas F (ed.) Fundamental Approaches to Software Engineering, Dusseldorf: Springer Verlag. 14th International Conference on Fundamental Approaches to Software Engineering, FASE 2011, 26.3.2011 - 3.4.2011, Saarbrucken, Germany, pp. 96-110.
Issue Date: 2011
Series/Report no.: Lecture Notes in Computer Science, 6603
Conference Name: 14th International Conference on Fundamental Approaches to Software Engineering, FASE 2011
Conference Dates: 2011-03-26T00:00:00Z
Conference Location: Saarbrucken, Germany
Abstract: Emergent phenomena occur due to the pattern of non-linear and distributed local interactions between the elements of a system over time. Surprisingly, agent based crowd models, in which the movement of each individual follows a limited set of simple rules, often re-produce quite closely the emergent behaviour of crowds that can be observed in reality. An example of such phenomena is the spontaneous self-organisation of drinking parties in the squares of cities in Spain, also known as "El Botellon" [20]. We revisit this case study providing an elegant stochastic process algebraic model in Bio-PEPA amenable to several forms of analyses, among which simulation and fluid flow analysis. We show that a fluid flow approximation, i.e. a deterministic reading of the average behaviour of the system, can provide an alternative and efficient way to study the same emergent behaviour as that explored in [20] where simulation was used instead. Besides empirical evidence, also an analytical justification is provided for the good correspondence found between simulation results and the fluid flow approximation.
Type: Conference Paper
Status: Author Version
Rights: Published in Lecture Notes in Computer Science by Springer Verlag.; The original publication is available at www.springerlink.com
URI: http://hdl.handle.net/1893/3555
URL: http://www.springerlink.com/content/lw5812w5k78744m8/
Affiliation: Istituto di Scienza e Tecnologie dell’Informazione
Istituto di Scienza e Tecnologie dell’Informazione
Computing Science - CSM Dept
University of Edinburgh

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