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Joint German/Austrian Conference on Artificial Intelligence (Künstliche Intelligenz)

KI 2017: KI 2017: Advances in Artificial Intelligence pp 359–365Cite as

Towards Simulation-Based Role Optimization in Organizations

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10505)

Abstract

The modern workplace is driven by a high amount of available information which can be observed in various domains, e.g., in Industry 4.0. Hence, the question arises: Which competences do actors need to build and efficient work environment? This paper proposes an simulation-based optimization approach to adapt role configurations for team work scenarios. The approach was tested using a multiagent-based job-shop-scheduling model to simulate the effects of various role configurations.

Keywords

  • Optimization
  • Multiagent-based simulation
  • Agent-based modeling
  • Team cognitions

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Acknowledgments

The project AdaptPRO: Adaptive Process and Role design in Organizations (TI 548/-1) is funded by the German Research Foundation (DFG) within the Priority Program “Intentional Forgetting in Organizations” (SPP 1921).

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Authors and Affiliations

  1. Business Informatics I, Trier University, Behringstraße 21, 54296, Trier, Germany

    Lukas Reuter, Jan Ole Berndt & Ingo J. Timm

Authors
  1. Lukas Reuter
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  2. Jan Ole Berndt
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  3. Ingo J. Timm
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Corresponding author

Correspondence to Lukas Reuter .

Editor information

Editors and Affiliations

  1. Fakultät für Informatik, Technische Universität Dortmund, Dortmund, Germany

    Gabriele Kern-Isberner

  2. FB Informatik, TU Darmstadt, Darmstadt, Hessen, Germany

    Dr. Johannes Fürnkranz

  3. FB Informatik, Universität Koblenz, Koblenz, Rheinland-Pfalz, Germany

    Matthias Thimm

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Reuter, L., Berndt, J.O., Timm, I.J. (2017). Towards Simulation-Based Role Optimization in Organizations. In: Kern-Isberner, G., Fürnkranz, J., Thimm, M. (eds) KI 2017: Advances in Artificial Intelligence. KI 2017. Lecture Notes in Computer Science(), vol 10505. Springer, Cham. https://doi.org/10.1007/978-3-319-67190-1_32

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  • DOI: https://doi.org/10.1007/978-3-319-67190-1_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67189-5

  • Online ISBN: 978-3-319-67190-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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