Bayesian networks, influence diagrams, and games in simulation metamodeling

 |  Login

Show simple item record

dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Virtanen, Kai, Dr.
dc.contributor.author Poropudas, Jirka
dc.date.accessioned 2012-08-31T07:43:45Z
dc.date.available 2012-08-31T07:43:45Z
dc.date.issued 2011
dc.identifier.isbn 978-952-60-4268-8 (PDF)
dc.identifier.isbn 978-952-60-4267-1 (printed)
dc.identifier.issn 1799-4942
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/5024
dc.description.abstract The Dissertation explores novel perspectives related to time and conflict in the context of simulation metamodeling referring to auxiliary models utilized in simulation studies. The techniques innovated in the Dissertation offer new analysis capabilities that are beyond the scope of the existing metamodeling approaches. In the time perspective, dynamic Bayesian networks (DBNs) allow the probabilistic representation of the time evolution of discrete event simulation by describing the probability distribution of the simulation state as a function of time. They enable effective what-if analysis where the state of the simulation at a given time instant is fixed and the conditional probability distributions related to other time instants are updated revealing the conditional time evolution. The utilization of influence diagrams (IDs) as simulation metamodels extends the use of the DBNs into simulation based decision making and optimization. They are used in the comparison of decision alternatives by studying their consequences represented by the conditional time evolution of the simulation. For additional analyses, random variables representing simulation inputs can be included in both the DBNs and the IDs. In the conflict perspective, the Dissertation introduces the game theoretic approach to simulation metamodeling. In this approach, existing metamodeling techniques are applied to the simulation analysis of game settings representing conflict situations where multiple decision makers pursue their own objectives. Game theoretic metamodels are constructed based on simulation data and used to study the interaction between the optimal decisions of the decision makers determining their best responses to each others' decisions and the equilibrium solutions of the game. Therefore, the game theoretic approach extends simulation based decision making and optimization into multilateral settings. In addition to the capabilities related to time and conflict, the techniques introduced in the Dissertation are applicable for most of the other goals of simulation metamodeling, such as validation of simulation models. The utilization of the new techniques is illustrated with examples considering simulation of air combat. However, they can also be applied to simulation studies conducted with any stochastic or discrete event simulation model. en
dc.format.extent Verkkokirja (527 KB, 33 s.)
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto University en
dc.relation.ispartofseries Aalto University publication series DOCTORAL DISSERTATIONS , 76/2011 en
dc.relation.haspart [Publication 1]: Jirka Poropudas and Kai Virtanen. 2011. Simulation metamodeling with dynamic Bayesian networks. European Journal of Operational Research, volume 214, number 3, pages 644-655. © 2011 Elsevier. By permission. en
dc.relation.haspart [Publication 2]: Jirka Poropudas and Kai Virtanen. 2010. Simulation metamodeling in continuous time using dynamic Bayesian networks. In: Björn Johansson, Sanjay Jain, Jairo Montoya-Torres, Joe Hugan, and Enver Yücesan (editors). Proceedings of the 2010 Winter Simulation Conference (WSC 2010). Baltimore, Maryland, USA. 5-8 December 2010. Pages 935-946. ISBN 978-1-4244-9864-2. © 2010 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 3]: Jirka Poropudas and Kai Virtanen. 2007. Analyzing air combat simulation results with dynamic Bayesian networks. In: Shane G. Henderson, Bahar Biller, Ming-Hua Hsieh, John Shortle, Jeffrey D. Tew, and Russell R. Barton (editors). Proceedings of the 2007 Winter Simulation Conference (WSC 2007). Washington DC, USA. 9-12 December 2007. Pages 1370-1377. ISBN 978-1-4244-1306-5. © 2007 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 4]: Jirka Poropudas and Kai Virtanen. 2009. Influence diagrams in analysis of discrete event simulation data. In: Manuel D. Rossetti, Raymond R. Hill, Björn Johansson, Ann Dunkin, and Ricki G. Ingalls (editors). Proceedings of the 2009 Winter Simulation Conference (WSC 2009). Austin, Texas, USA. 13-16 December 2009. Pages 696-708. ISBN 978-1-4244-5771-7. © 2009 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 5]: Jirka Poropudas and Kai Virtanen. 2010. Game-theoretic validation and analysis of air combat simulation models. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, volume 40, number 5, pages 1057-1070. © 2010 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 6]: Jouni Pousi, Jirka Poropudas, and Kai Virtanen. 2010. Game theoretic simulation metamodeling using stochastic kriging. In: Björn Johansson, Sanjay Jain, Jairo Montoya-Torres, Joe Hugan, and Enver Yücesan (editors). Proceedings of the 2010 Winter Simulation Conference (WSC 2010). Baltimore, Maryland, USA. 5-8 December 2010. Pages 1456-1467. ISBN 978-1-4244-9864-2. © 2010 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.title Bayesian networks, influence diagrams, and games in simulation metamodeling en
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.school Perustieteiden korkeakoulu fi
dc.contributor.department Matematiikan ja systeemianalyysin laitos fi
dc.contributor.department Department of Mathematics and Systems Analysis en
dc.subject.keyword simulation en
dc.subject.keyword simulation metamodeling en
dc.subject.keyword discrete event simulation en
dc.subject.keyword stochastic simulation en
dc.subject.keyword Bayesian networks en
dc.subject.keyword influence diagrams en
dc.subject.keyword tech en
dc.subject.keyword game theory en
dc.identifier.urn URN:ISBN:978-952-60-4268-8
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en
dc.contributor.supervisor Hämäläinen, Raimo P., Prof.


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search archive


Advanced Search

article-iconSubmit a publication

Browse

My Account