Nature of Computation and Communication. Second International Conference, ICTCC 2016, Rach Gia, Vietnam, March 17-18, 2016, Revised Selected Papers

Research Article

Toward an Agent-Based and Equation-Based Coupling Framework

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  • @INPROCEEDINGS{10.1007/978-3-319-46909-6_28,
        author={Huynh Quang Nghi and Tri Nguyen-Huu and Arnaud Grignard and Hiep Xuan Huynh and Alexis Drogoul},
        title={Toward an Agent-Based and Equation-Based Coupling Framework},
        proceedings={Nature of Computation and Communication. Second International Conference, ICTCC 2016, Rach Gia, Vietnam, March 17-18, 2016, Revised Selected Papers},
        proceedings_a={ICTCC},
        year={2017},
        month={1},
        keywords={Equation-based model Agent-based model Coupling framework Simulation platform Epidemiology},
        doi={10.1007/978-3-319-46909-6_28}
    }
    
  • Huynh Quang Nghi
    Tri Nguyen-Huu
    Arnaud Grignard
    Hiep Xuan Huynh
    Alexis Drogoul
    Year: 2017
    Toward an Agent-Based and Equation-Based Coupling Framework
    ICTCC
    Springer
    DOI: 10.1007/978-3-319-46909-6_28
Huynh Quang Nghi,*, Tri Nguyen-Huu, Arnaud Grignard, Hiep Xuan Huynh, Alexis Drogoul
    *Contact email: hqnghi88@gmail.com

    Abstract

    The ecology modeling generally opposes two class of models, equations based models and multi-agents based models. Mathematical models allow predicting the long-term dynamics of the studied systems. However, the variability between individuals is difficult to represent, what makes these more suitable models for large and homogeneous populations. Multi-agent models allow representing the attributes and behavior of each individual and therefore provide a greater level of detail. In return, these systems are more difficult to analyze. These approaches have often been compared, but rarely used simultaneously. We propose a hybrid approach to couple equations models and agent-based models, as well as its implementation on the modeling platform Gama [7]. We focus on the representation of a classical theoretical epidemiological model (SIR model) and we illustrate the construction of a class of models based on it.