An agent-based simulation tool for participatory training environment: Application to rodent control campaign
Article No.: 13, Pages 1 - 7
Abstract
In this paper we present a general idea of a participatory training environment in a context of multi-agent participatory simulation applied to rodent control. In a first step, we focus on the agent-based simulation tool that embeds ecosystem models such as rodent dynamics, weather variation and land occupation. The general idea of our training environment is based on (1) an agent based ecosystems simulation as well as actor's avatar interacting with the simulation; and (2) a negotiation based skill evaluation of the actors' behaviors during the simulation. This paper is a key piece of how the combination of these two approaches can help improving rodent control efficiency.
References
[1]
Singleton, G. R., Leirs, H., Hinds, L. A., & Zhang, Z. (1999). Ecologically-based management of rodent pests--re-evaluating our approach to an old problem. Ecologically-based Management of Rodent Pests. Australian Centre for International Agricultural Research (ACIAR), Canberra, 17--29.
[2]
Fiedler, L.A. 1988. Rodent problems in Africa. Pages 35--65 in Prakash, I., ed. 1988. Rodent Pest Management. CRC Press, Boca Raton, FL USA. 480 p.
[3]
Leirs, H., Verhagen, R., Verheyen, W., Mwanjabe, P., & Mbise, T. (1996). Forecasting rodent outbreaks in Africa: an ecological basis for Mastomys control in Tanzania. Journal of Applied Ecology, 937--943.
[4]
Drouai, H., Belhamra, M., & Mimeche, F. (2018). Inventory and distribution of the rodents in Aurès Mountains and Ziban oasis (Northeast of Algeria). In Anales de Biología (Vol. 40, pp. 47--55).
[5]
Fiedler, L. A. (2018). Rodent problems in Africa. In Rodent pest management (pp. 45--76). CRC Press.
[6]
FAO 2007. "Information and Communication Technology (ICT) in Agriculture." Technical Report. Food and Agriculture Organisation of the United Nations. Retrieved from:Erreur ! Référence de lien hypertexte non valide.
[7]
Abdon, B., Raab, R., & Ninomiya, S. (2008). eLearning for international agriculture development: Dealing with challenges. International Journal of Education and Development using ICT, 4(1), 80--94.
[8]
Tata, J. S., & McNamara, P. E. (2018). Impact of ICT on agricultural extension services delivery: evidence from the Catholic Relief Services SMART skills and Farmbook project in Kenya. The Journal of Agricultural Education and Extension, 24(1), 89--110.
[9]
P. R. Brown, G. R. Singleton, G. A. Norton and D. Thompson, "Mouser (Version 1.0): a decision tool for managing mice", 12th Australasian Vertebrate Pest Conference, 21-25 May 2001, Melbourne, Victoria.
[10]
Puhalo, D., Klobučar, A., & Benić, N. (2013). Modern application of information and communication technologies-rodents and mosquitoes in a digital world. In Zbornik Radova 25. Znanstveno Stručno Edukativni Seminar DDD i ZUPP 2013: Djelatnost dezinfekcije, dezinsekcije, deratizacije i zaštite uskladištenih, poljoprivrednih proizvoda, Split, Republike Hrvatske, 2. do 5. travnja 2013 (pp. 99--113). Korunić doo Zagreb.
[11]
N. C. Stenseth et al. "Mice, rats and people: the bio-economics of agricultural rodent pests". Front. Ecol. Environ 2003. 1, 367--375.
[12]
J. E. Brooks, P. Sultana and R. M. Poché, "Damage by Bandicota bengalensis to growing wheat in Bangladesh and methods of control". Acta Zool. Fennica 2003, 173, 135--137.
[13]
G. A. Mendoza and R. Prabhu, "Combining participatory modeling and multi-criteria analysis for community-based forest management", Forest Ecol. Manage. 207, 2005, 145--156.
[14]
Wesselow, M., & Stoll-Kleemann, S. (2018). Role-playing games in natural resource management and research: Lessons learned from theory and practice. The Geographical Journal.
[15]
Barreteau, O., Bots, P., Daniell, K., Etienne, M., Perez, P., Barnaud, C., ... & Trebuil, G. (2017). Participatory approaches. In Simulating Social Complexity (pp. 253--292). Springer, Cham.
[16]
Dolinska, A. (2017). Bringing farmers into the game. Strengthening farmers' role in the innovation process through a simulation game, a case from Tunisia. Agricultural Systems, 157, 129--139.
[17]
Salvini, G., Van Paassen, A., Ligtenberg, A., Carrero, G. C., & Bregt, A. K. (2016). A role-playing game as a tool to facilitate social learning and collective action towards Climate Smart Agriculture: Lessons learned from Apuí, Brazil. Environmental Science & Policy, 63, 113--121.
[18]
Kerselaers, E., Rogge, E., Lauwers, L., & Van Huylenbroeck, G. (2015). Decision support for prioritising of land to be preserved for agriculture: can participatory tool development help?. Computers and Electronics in Agriculture, 110, 208--220.
[19]
E. Kuntashula and P. L. Mafongoya, "Farmer participatory evaluation of agroforestry trees in eastern Zambia", Agric. Syst 2005. 84, 39--53.
[20]
Castella, J. C., Trung, T. N., & Boissau, S. (2005). Participatory simulation of land-use changes in the northern mountains of Vietnam: the combined use of an agent-based model, a role-playing game, and a geographic information system. Ecology and Society, 10(1).
[21]
Bonte, B., Bousquet, F., Müller, J. P., Pellegrin, F., & Bonato, O. (2008). Construction d'une plateforme de formalisation et de simulation de la problématique des risques émergents (maladies et bio-invasions) et de leur gestion dans le domaine phytosanitaire.
[22]
May, R. M. (2001). Stability and complexity in model ecosystems (Vol. 6). Princeton university press.
[23]
Coll, M., Akoglu, E., Arreguin-Sanchez, F., Fulton, E. A., Gascuel, D., Heymans, J. J., ... & Shannon, L. J. (2015). Modelling dynamic ecosystems: venturing beyond boundaries with the Ecopath approach. Reviews in Fish Biology and Fisheries, 25(2), 413--424.
[24]
Leirs, H., Stenseth, N. C., Nichols, J. D., Hines, J. E., Verhagen, R., & Verheyen, W. (1997). Stochastic seasonality and nonlinear density-dependent factors regulate population size in an African rodent. Nature, 389(6647), 176.
[25]
Leirs, H. (1999). 19. Populations of African Rodents: Models and the Real World.
[26]
Stenseth, N. C., Leirs, H., Mercelis, S., & Mwanjabe, P. (2001). Comparing strategies for controlling an African pest rodent: an empirically based theoretical study. Journal of Applied Ecology, 38(5), 1020--1031.
[27]
Leslie, P. H. (1945). On the use of matrices in certain population mathematics. Biometrika, 183--212.
[28]
Yoccoz, N. G., Nakata, K., Stenseth, N. C., & Saitoh, T. (1998). The demography ofClethrionomys rufocanus: from mathematical and statistical models to further field studies. Researches on Population Ecology, 40(1), 107--121.
[29]
Meurisse, T. (2004). Simulation multi-agent: du modèle à l'opérationnalisation (Doctoral dissertation, Paris 6).
[30]
Petrusewicz, K., & Macfadyen, A. (1970). Productivity of terrestrial animals. Principles and methods. Productivity of terrestrial animals. Principles and methods. (13).
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- An agent-based simulation tool for participatory training environment: Application to rodent control campaign
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December 2018
201 pages
ISBN:9781450361019
DOI:10.1145/3330089
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Published: 26 December 2018
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ICSENT 2018
ICSENT 2018: 7th International Conference on Software Engineering and New Technologies
December 26 - 28, 2018
Hammamet, Tunisia
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