License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.12.10.1
URN: urn:nbn:de:0030-drops-178196
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/17819/
Go back to Dagstuhl Reports

Cai, Wentong ; Carothers, Christopher ; Nicol, David M. ; Uhrmacher, Adelinde M.
Weitere Beteiligte (Hrsg. etc.): Wentong Cai and Christopher Carothers and David M. Nicol and Adelinde M. Uhrmacher

Computer Science Methods for Effective and Sustainable Simulation Studies (Dagstuhl Seminar 22401)

pdf-format:
dagrep_v012_i010_p001_22401.pdf (6 MB)

Abstract

This report documents the program and the (preliminary) outcomes of Dagstuhl Seminar 22401 "Computer Science Methods for Effective and Sustainable Simulation Studies". The seminar has been dedicated to addressing central methodological challenges in conducting effective and sustainable simulation studies. Lightning talks provided the opportunity for participants to present their current research and ideas to advance methodological research in modeling and simulation. However, the lion’s share of the seminar was dedicated to working groups. One working group investigated how machine learning and modeling and simulation can be effectively integrated (Intelligent Modeling and Simulation Lifecycle). Another working group focused on methodological challenges to support policy via simulation (Policy by simulation: seeing is believing for interactive model co-creation and effective intervention). A third working group identified 4 challenges closely tied to the quest for sustainable simulation studies (Context, composition, automation, and communication - towards sustainable simulation studies) thereby, focusing on the role of model-based approaches and related methods.

BibTeX - Entry

@Article{cai_et_al:DagRep.12.10.1,
  author =	{Cai, Wentong and Carothers, Christopher and Nicol, David M. and Uhrmacher, Adelinde M.},
  title =	{{Computer Science Methods for Effective and Sustainable Simulation Studies (Dagstuhl Seminar 22401)}},
  pages =	{1--60},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{12},
  number =	{10},
  editor =	{Cai, Wentong and Carothers, Christopher and Nicol, David M. and Uhrmacher, Adelinde M.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/17819},
  URN =		{urn:nbn:de:0030-drops-178196},
  doi =		{10.4230/DagRep.12.10.1},
  annote =	{Keywords: Modeling, simulation, high performance computing, machine learning, visual analytics}
}

Keywords: Modeling, simulation, high performance computing, machine learning, visual analytics
Collection: DagRep, Volume 12, Issue 10
Issue Date: 2023
Date of publication: 03.05.2023

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI