Statistical analysis of CARMA models: An advanced tutorial

Vashti Galpin, Anastasis Georgoulas, Michele Loreti, Andrea Vandin

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

CARMA (Collective Adaptive Resource-sharing Markovian Agents) is a process-algebra-based quantitative language developed for the modeling of collective adaptive systems. A CARMA model consists of an environment in which a collective of components with attribute stores interact via unicast and broadcast communication, providing a rich modeling formalism. The semantics of a CARMA model are given by a continuous-time Markov chain which can be simulated using the CARMA Eclipse Plug-in. Furthermore, statistical model checking can be applied to the trajectories generated through simulation using the MultiVeStA tool. This advanced tutorial will introduce some of the theory behind CARMA and MultiVeStA as well as demonstrate its application to collective adaptive system modeling.

Original languageEnglish
Title of host publicationProceedings of the 2018 Winter Simulation Conference
PublisherIEEE
Publication date31 Jan 2019
Pages395-409
Article number8632456
ISBN (Electronic)9781538665725
DOIs
Publication statusPublished - 31 Jan 2019
Event2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden
Duration: 9 Dec 201812 Dec 2018

Conference

Conference2018 Winter Simulation Conference, WSC 2018
Country/TerritorySweden
CityGothenburg
Period09/12/201812/12/2018
SponsorRockwell Automation Headquarters, Bayer, Chalmers University of Technology, Simio LLC, The AnyLogic Company

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