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

Authors Wentong Cai, Christopher Carothers, David M. Nicol, Adelinde M. Uhrmacher and all authors of the abstracts in this report



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Author Details

Wentong Cai
  • Nanyang TU - Singapore, SG
Christopher Carothers
  • Rensselaer Polytechnic Institute - Troy, US
David M. Nicol
  • University of Illinois - Urbana Champaign, US
Adelinde M. Uhrmacher
  • Universität Rostock, DE
and all authors of the abstracts in this report

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Wentong Cai, Christopher Carothers, David M. Nicol, and Adelinde M. Uhrmacher. Computer Science Methods for Effective and Sustainable Simulation Studies (Dagstuhl Seminar 22401). In Dagstuhl Reports, Volume 12, Issue 10, pp. 1-60, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/DagRep.12.10.1

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.

Subject Classification

ACM Subject Classification
  • Computing methodologies
Keywords
  • Modeling
  • simulation
  • high performance computing
  • machine learning
  • visual analytics

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