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Probabilistic Modelling and Analysis of a Fish Population

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Software Engineering and Formal Methods (SEFM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9509))

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Abstract

The fish stock of the common sole in the Adriatic Sea has been analysed by agent-based modelling and simulation techniques as an integration of other classical stock assessment models. In this work we start investigating also about the formal probabilistic modelling of our case study in order to extract valuable biological information from available formal verification techniques. In particular, a PRISM model for the common sole is developed and some initial results are discussed.

This work has been supported by the RITMARE Flagship Project and by the PRIN Project CINA (prot. 2010LHT4KM), both funded by the Italian MIUR.

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Notes

  1. 1.

    The full PRISM model together with some variants with which we experimented is available at https://dl.dropboxusercontent.com/u/33462615/Soles.zip.

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Authors and Affiliations

  1. School of Science and Technology, University of Camerino, Via del Bastione, 1, 62032, Camerino, Italy

    Luca Tesei, Cesar A. Nieto Coria & Emanuela Merelli

  2. National Research Council - Institute of Marine Sciences Ancona, Largo Fiera della Pesca, 2, 60125, Ancona, Italy

    Giuseppe Scarcella

  3. CINFAI, Consorzio Interuniversitario Nazionale per la Fisica Delle Atmosfere e delle Idrosfere, Sezione di Camerino, Via del Bastione, 1, 62032, Camerino, Italy

    Luca Tesei, Cesar A. Nieto Coria & Emanuela Merelli

  4. e-Lios (e-Linking Online Systems) S.r.l., Via Le Mosse, 22, 62032, Camerino, Italy

    Chiara Cini

Authors
  1. Chiara Cini
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  2. Luca Tesei
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  3. Giuseppe Scarcella
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  4. Cesar A. Nieto Coria
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  5. Emanuela Merelli
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Correspondence to Luca Tesei .

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Editors and Affiliations

  1. Interdisciplinary Centre for ICT Se, University of Luxembourg (UL)., Luxembourg

    Domenico Bianculli

  2. University of York, York, United Kingdom

    Radu Calinescu

  3. LS Software Engineering, RWTH Aachen Universität, Aachen, Nordrhein-Westfalen, Germany

    Bernhard Rumpe

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Cini, C., Tesei, L., Scarcella, G., Nieto Coria, C.A., Merelli, E. (2015). Probabilistic Modelling and Analysis of a Fish Population. In: Bianculli, D., Calinescu, R., Rumpe, B. (eds) Software Engineering and Formal Methods. SEFM 2015. Lecture Notes in Computer Science(), vol 9509. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49224-6_16

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  • DOI: https://doi.org/10.1007/978-3-662-49224-6_16

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