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A Multi-Agent Model for Describing Transhumance in North Cameroon: Comparison of Different Rationality to Develop a Routine

Author

Listed:
  • Juliette Rouchier

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • François Bousquet
  • Mélanie Requier-Desjardins
  • Martine Antona

    (Cirad-TERA ERE - Programme Espace et ressources - Cirad-TERA - Département Territoires, Environnement et Acteurs - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement)

Abstract

This paper introduces an application using multi-agent system to model an artificial society. The work follows a field research in economics in Cameroon about the behavior of nomad herdsmen securing their access to rangelands. Two central elements were stressed: regularity in meetings and flexibility while facing problems. Experiments run through simulations, testing two rationales: choices based on the notion of cost, or herdsmen taking into account the history of meetings. The system successfully shows regular dynamics, and huge differences are observed, depending on the rationality used. We conclude on the importance of the rationality described in modeling a system.

Suggested Citation

  • Juliette Rouchier & François Bousquet & Mélanie Requier-Desjardins & Martine Antona, 2001. "A Multi-Agent Model for Describing Transhumance in North Cameroon: Comparison of Different Rationality to Develop a Routine," Post-Print halshs-00550482, HAL.
    • Handle: RePEc:hal:journl:halshs-00550482
    DOI: 10.1016/S0165-1889(00)00035-X
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    Citations

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    Cited by:

    1. Joïlle Noailly & Jeroen C.J.M. van den Bergh & Cees A. Withagen, 2003. "Evolution of harvesting strategies: replicator and resource dynamics," Journal of Evolutionary Economics, Springer, vol. 13(2), pages 183-200, April.
    2. Juliette Rouchier, 2013. "The Interest of Having Loyal Buyers in a Perishable Market," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 151-170, February.
    3. Muhammad Hadi Saputra & Han Soo Lee, 2019. "Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton," Sustainability, MDPI, vol. 11(11), pages 1-16, May.
    4. Rosaria Conte & Bruce Edmonds & Scott Moss & R. Keith Sawyer, 2001. "Sociology and Social Theory in Agent Based Social Simulation: A Symposium," Computational and Mathematical Organization Theory, Springer, vol. 7(3), pages 183-205, October.
    5. Narine Udumyan & Juliette Rouchier & Dominique Ami, 2014. "Integration of Path-Dependency in a Simple Learning Model: The Case of Marine Resources," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 199-231, February.
    6. Stefano Balbi & Carlo Giupponi, 2009. "Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability," Working Papers 2009_15, Department of Economics, University of Venice "Ca' Foscari".
    7. Anthony Patt & Bernd Siebenhüner, 2005. "Agent Based Modeling and Adaption to Climate Change," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 74(2), pages 310-320.

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