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New Hybrid Approach Multi-agents System and Case Based Reasoning for Management of Common Renewable Resources

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Innovations in Smart Cities Applications Edition 3 (SCA 2019)

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Abstract

In this paper, we present a new hybrid approach multi-agents system and Case-Based Reasoning (CBR). We have designed a generic and scalable class diagram to develop complex multi-agent systems [3] for Decision Support System based on CBR to predict and anticipate an environmental risk. Our approach inherits from Model Driven Architecture (MDA [11]), which aims to design, develop and implement models of multi-agent systems that we build from AUML. The source code of the models is generated by an open source tool called AndroMDA [13]. The model and source code will be used to design and develop applications to implement and simulate multi-agent models for Management of Common Renewable Resources [4].

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Authors and Affiliations

  1. LIST Laboratory, FST of Tangier, UAE, Tanger, Morocco

    Mohamed Kouissi & El Mokhtar En-Naimi

Authors
  1. Mohamed Kouissi
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  2. Nihad El Ghouch
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  3. El Mokhtar En-Naimi
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Corresponding author

Correspondence to El Mokhtar En-Naimi .

Editor information

Editors and Affiliations

  1. Faculty of Sciences and Techniques of Tangier, Mediterranean Association of Sciences and Technologies, Tangier, Morocco

    Mohamed Ben Ahmed

  2. Faculty of Sciences and Techniques of Tangier, Abdelmalek Essaadi University, Tangier, Morocco

    Anouar Abdelhakim Boudhir

  3. Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal

    Domingos Santos

  4. Hassania School of Public Works, Casablanca, Morocco

    Mohamed El Aroussi

  5. Computer Engineering Department, Faculty of Engineering, Karabuk University, Karabük, Turkey

    İsmail Rakıp Karas

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Kouissi, M., El Ghouch, N., En-Naimi, E.M. (2020). New Hybrid Approach Multi-agents System and Case Based Reasoning for Management of Common Renewable Resources. In: Ben Ahmed, M., Boudhir, A., Santos, D., El Aroussi, M., Karas, İ. (eds) Innovations in Smart Cities Applications Edition 3. SCA 2019. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-37629-1_52

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  • DOI: https://doi.org/10.1007/978-3-030-37629-1_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37628-4

  • Online ISBN: 978-3-030-37629-1

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