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Data Management in Multi-Agent Simulation Systems

dc.contributor.authorGlake, Daniel
dc.contributor.authorPanse, Fabian
dc.contributor.authorRitter, Norbert
dc.contributor.authorClemen, Thomas
dc.contributor.authorLenfers, Ulfia
dc.contributor.editorKai-Uwe Sattler
dc.contributor.editorMelanie Herschel
dc.contributor.editorWolfgang Lehner
dc.date.accessioned2021-03-16T07:57:11Z
dc.date.available2021-03-16T07:57:11Z
dc.date.issued2021
dc.description.abstractMulti-agent simulations are an upcoming trend to deal with the urgent need to predict complex situations as they arise in many real-life areas, such as disaster or traffic management. Such simulations require large amounts of heterogeneous data ranging from spatio-temporal to standard object properties. This and the increasing demand for large scale and real-time simulations pose many challenges for data management. In this paper, we present the architecture of a typical agent-based simulation system, describe several data management challenges that arise in such a data ecosystem, and discuss their current solutions within our multi-agent simulation system MARS.en
dc.identifier.doi10.18420/btw2021-22
dc.identifier.isbn978-3-88579-705-0
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/35806
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBTW 2021
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-311
dc.subjectMulti-agent simulations
dc.subjectSpatio-temporal data
dc.subjectPolyglot data management
dc.titleData Management in Multi-Agent Simulation Systemsen
gi.citation.endPage436
gi.citation.startPage423
gi.conference.date13.-17. September 2021
gi.conference.locationDresden
gi.conference.sessiontitle(Industrial) Use Cases & Applications

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