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Quantitative Abstractions for Collective Adaptive Systems

Vandin, Andrea and Tribastone, Mirco Quantitative Abstractions for Collective Adaptive Systems. In: Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems : 16th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2016, Bertinoro, Italy, June 20-24, 2016, Advanced Lectures. Lecture Notes in Computer Science (9700). Springer International Publishing, Cham, pp. 202-232. ISBN 978-3-319-34095-1 (2016)

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Abstract

Collective adaptive systems (CAS) consist of a large number of possibly heterogeneous entities evolving according to local interactions that may operate across multiple scales in time and space. The adaptation to changes in the environment, as well as the highly dispersed decision-making process, often leads to emergent behaviour that cannot be understood by simply analysing the objectives, properties, and dynamics of the individual entities in isolation. As with most complex systems, modelling is a phase of crucial importance for the design of new CAS or the understanding of existing ones. Elsewhere in this volume the typical workflow of formal modelling, analysis, and evaluation of a CAS has been illustrated in detail. In this chapter we treat the problem of efficiently analysing large-scale CAS for quantitative properties. We review algorithms to automatically reduce the dimensionality of a CAS model preserving modeller-defined state variables, with focus on descriptions based on systems of ordinary differential equations. We illustrate the theory in a tutorial fashion, with running examples and a number of more substantial case studies ranging from crowd dynamics, epidemiology and biological systems.

Item Type: Book Section
Identification Number: 10.1007/978-3-319-34096-8_7
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Research Area: Computer Science and Applications
Depositing User: Caterina Tangheroni
Date Deposited: 13 Jul 2016 09:43
Last Modified: 13 Jul 2016 09:43
URI: http://eprints.imtlucca.it/id/eprint/3516

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