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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2017: Artificial Intelligence and Soft Computing pp 599–608Cite as

Simulation of Multi-agent Systems with Alvis Toolkit

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

Abstract

The paper presents a method of using the Alvis formal modelling language and related software to model and simulate multi-agent systems. The approach has been illustrated with an example of a railway traffic management system for a real train station. One of the main advantages of this approach is the possibility of including artificial intelligence (AI) systems encoded in Haskell into Alvis models. Moreover, Alvis models can be developed at the level very close to the final implementation of the corresponding real system. Thus simulation logs can be treated as a virtual prototype logs.

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Authors and Affiliations

  1. Department of Applied Computer Science, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059, Kraków, Poland

    Marcin Szpyrka, Piotr Matyasik, Łukasz Podolski & Michał Wypych

Authors
  1. Marcin Szpyrka
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  2. Piotr Matyasik
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  3. Łukasz Podolski
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  4. Michał Wypych
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Corresponding author

Correspondence to Marcin Szpyrka .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2017 Springer International Publishing AG

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Szpyrka, M., Matyasik, P., Podolski, Ł., Wypych, M. (2017). Simulation of Multi-agent Systems with Alvis Toolkit. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_54

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  • DOI: https://doi.org/10.1007/978-3-319-59060-8_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59059-2

  • Online ISBN: 978-3-319-59060-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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