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2nd International ICST Conference on Simulation Tools and Techniques

Research Article

Hybrid MAS GIS Mediterranean backcountry tourism economy modeling methodology

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  • @INPROCEEDINGS{10.4108/ICST.SIMUTOOLS2009.5607,
        author={Dominique Urbani and Marielle Delhom},
        title={Hybrid MAS GIS Mediterranean backcountry tourism economy modeling methodology},
        proceedings={2nd International ICST Conference on Simulation Tools and Techniques},
        publisher={ICST},
        proceedings_a={SIMUTOOLS},
        year={2010},
        month={5},
        keywords={Distributed artificial intelligence multi-agent system model simulation geographic information system environmental system tourism decision support system tourism Mediterranean Corsica.},
        doi={10.4108/ICST.SIMUTOOLS2009.5607}
    }
    
  • Dominique Urbani
    Marielle Delhom
    Year: 2010
    Hybrid MAS GIS Mediterranean backcountry tourism economy modeling methodology
    SIMUTOOLS
    ICST
    DOI: 10.4108/ICST.SIMUTOOLS2009.5607
Dominique Urbani1,*, Marielle Delhom1,*
  • 1: University of Corsica, UMR CNRS 6134 – SPE LAB, Quartier Grosseti - 20250 Corte - France + 33 4 95 45 01 60
*Contact email: durbani@laposte.net, delhom@univ-Corse.fr

Abstract

Submitted to the combination of the sun immigration pressure and the decline of their traditional economy, the Mediterranean islands are in a paradoxical position. Indeed, while the populations on the shores are growing, the countryside is endangered involving the desertification. In this paper we shall present a methodology to build a distributed artificial intelligence based model dedicated to the countryside economy and its interactions with the growing touristic coastal areas through the flow of tourists. Organizing the economic system into a hierarchy, following a multi-agent approach, we build a generic model of each system’s stakeholders from our observations. We propose a methodology to model the exchanges between the countryside’s visitors and the local economy’s players. Using a geographic information system, we explicit how to take advantage of the spatiotemporal ground data to fit the simulations to the specificities of each targeted site. Finally we present a first application on a Corsican case.

Keywords
Distributed artificial intelligence multi-agent system model simulation geographic information system environmental system tourism decision support system tourism Mediterranean Corsica.
Published
2010-05-16
Publisher
ICST
Modified
2010-05-16
http://dx.doi.org/10.4108/ICST.SIMUTOOLS2009.5607
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