Exploring Parameter Tuning for Analysis and Optimization of a Computational Model

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Abstract

Computational models of human processes are used for many different purposes and in many different types of applications. A common challenge in using such models is to find suitable parameter values. In many cases, the ideal parameter values are those that yield the most realistic simulation results. However, there are situations in which the goodness of fit is not the main or only criterion to evaluate the appropriateness of a model, but where other aspects of the model behavior are also relevant. This is often the case when computational models are employed in real-life applications, such as mHealth systems. In this paper, we explore how parameter tuning techniques can be used to analyze the behavior of computational models systematically and to investigate the reasons behind the observed behavior. We study a computational model of psychosocial influences on physical activity behavior as an in-depth use case. In this particular case, an important measure of the feasibility of the model is the diversity in the simulation outcomes. This novel application of parameter tuning techniques for analysis and understanding of model behavior is transferable to other cases, and is therefore a valuable new approach in the toolset of computational modelers.
Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence: From Theory to Practice - 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, Proceedings
PublisherSpringer/Verlag
Pages341-352
Number of pages12
Volume10351 LNCS
ISBN (Print)9783319600444
DOIs
Publication statusPublished - 27 Jun 2017
Event30th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, IEA/AIE 2017 - Arras, France
Duration: 27 Jun 201730 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10351 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference30th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, IEA/AIE 2017
CountryFrance
CityArras
Period27/06/1730/06/17

Keywords

  • mHealth systems
  • Behavior change
  • Computational modeling
  • Dynamic modeling
  • Model analysis
  • Model optimization
  • Parameter tuning

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  • Cite this

    Mollee, J. S., Fernandes de Mello Araujo, E., & Klein, M. C. A. (2017). Exploring Parameter Tuning for Analysis and Optimization of a Computational Model. In Advances in Artificial Intelligence: From Theory to Practice - 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, Proceedings (Vol. 10351 LNCS, pp. 341-352). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10351 LNCS). Springer/Verlag. https://doi.org/10.1007/978-3-319-60045-1_36