Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/1584
Appears in Collections:Computing Science and Mathematics Technical Reports
Peer Review Status: Refereed
Title: Deriving Mean Field Equations from Large Process Algebra Models
Authors: McCaig, Chris
Norman, Rachel
Shankland, Carron
Contact Email: ran@cs.stir.ac.uk
Citation: McCaig C, Norman R & Shankland C (2008) Deriving Mean Field Equations from Large Process Algebra Models. Technical Report CSM, 175. Department of Computing Science and Mathematics, University of Stirling.
Issue Date: Mar-2008
Publisher: Department of Computing Science and Mathematics, University of Stirling
Series/Report no.: Technical Report CSM, 175
Abstract: In many domain areas the behaviour of a system can be described at two levels: the behaviour of individual components, and the behaviour of the system as a whole. Often deriving one from the other is impossible, or at least intractable, especially when realistically large systems are considered. Here we present a rigorous algorithm which, given an individual based model in the process algebra WSCCS describing the components of a system and the way they interact, can produce a system of mean field equations which describe the mean behaviour of the system as a whole. This transformation circumvents the state explosion problem, allowing us to handle systems of any size by providing an approximation of the system behaviour. From the mean field equations we can investigate the transient dynamics of the system. This approach was motivated by problems in biological systems, but is applicable to distributed systems in general.
Type: Technical Report
URL: http://www.cs.stir.ac.uk/research/publications/techreps/
URI: http://hdl.handle.net/1893/1584
Affiliation: University of Stirling
Computing Science - CSM Dept
Computing Science - CSM Dept

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