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On The Joint Modeling of The Behavior of Social Insects and Their Interaction With Environment by Taking Into Account Physical Phenomena Like Anisotropic Diffusion

Cazin, Nicolas and Histace, Aymeric and Picard, David and Gaudou, Benoit On The Joint Modeling of The Behavior of Social Insects and Their Interaction With Environment by Taking Into Account Physical Phenomena Like Anisotropic Diffusion. (2015) In: 13th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2015), 3 June 2015 - 4 June 2015 (Salamanca, Spain).

(Document in English)

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Official URL: http://dx.doi.org/10.1007/978-3-319-19033-4_13


This work takes place in the framework of GEODIFF project (funded by CNRS) and deals with the general issue of the social behavior modeling of pest insects with a particular focus on Bark Beetles. Bark Beetles are responsible for pine trees devastation in North America since 2005. In order to stem the problem and to apply an adapted strategy, one should be able to predict the evolution of the population of Bark Beetles. More precisely, a model taking into account a given population of insects (a colony) interacting with its environment, the forest ecosystem, would be very helpful. In a previous work, we aimed to model diffusive phenomenons across the environment using a simple reactive Multi-agent System. Bark beetle use pheromones as a support for recruitment of other bark beetles in the neighborhood in order to achieve a mass attack over a tree. They are first attracted by the ethanol or other phytopheromones emitted by a sick, stressed or dead tree and reinforce the presence of other individuals amongst the targeted tree. Both ethanol and semiochemicals are transported through the forest thanks to the wind, thermic effects and this advection phenomenon is modulated by the topology of the environment, tree and other obstacles distribution. In other words, the environment is involved in the process of a bark beetle attack. The first modeling we used to tackle our objective was not spatially explicit as long as free space propagation only was taken into account (isotropic phenomenon) with no constraint imposed by the environment such as wind. This article is intended to take into account such physical phenomenons and push the modeling one step further by providing predictions driven by measures provided by a Geographical Information System.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to Springer editor. This papers appears in Volume 524 Communications in Computer and Information Science ISSN : 1865-0929 ISBN: 978-3-319-19032-7. The original PDF is available at: http://link.springer.com/chapter/10.1007%2F978-3-319-19033-4_13
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Université de Cergy-Pontoise (FRANCE)
Laboratory name:
Deposited On:01 Sep 2016 12:20

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