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or located in some few protected areas. (Brandouy,
et al., 2012).
3.1.2 SIEGMAS
Farmers (deviant or not) generally aim to make their
land as profitable as possible to cover several costs
(e.g. investment, maintenance). A farmer can choose
to spread legally his cultivation via the purchase of
new plots or reaching the legally maximum allowed
use of natural resources. In fact, the management's
transfers grant the farmer through the basis
community some right of cultivation of some natural
resources. However, the farmer can be a deviant by
farming illegally some plots of natural and forester
resources.
This model is mainly focused on the farmers and
the government and their interactions in relation to
the forester and natural resources as well as the
resources produced on the farms.
The model SIEGMAS has been implemented
under the platform of the programming called
NetLogo. The farmers can respect or infringe the
legislation towards the protection of natural
resources. The controls or the rupture can identify
the transgressions. Authorities grant some individual
sanctions to the deviants. Thus, not any collective
sanction impacts the respectful farmers of the
legislation. The farmers set themselves up in order to
increase their productivity and to perpetuate the trust
that the state authorities grant (or to avoid the
sanctions for everything by having a nearby context
in favor of their activity (Wade, 1987).
For the sanctions, the deviants want to exploit
randomly the lands being around his exploitations,
even those created illegally. At each iteration, the
government notes a random number of lands
illegally exploited and looks for the one who created
the exploitation. After launching several times the
simulation with different values of configurations, it
appears by observing the variation of the rate of
deviants that if the government controls the
management's transfers correctly, the sanctions are
well applied. The presence of the deviants increases
land deterioration. Some deviants however manage
to avoid sanctions and run some untaxed incomes.
Nevertheless, the application of a sanction to the
deviants rebalances the system so that the deviants
cannot get any profits from the illegal practice of
agriculture or the exploitation of natural resources.
Therefore, individual behaviors impact the collective
behaviors if a farmer knows the machinations of his
neighboring. The farmer generally grants his trust to
his neighbor as long as it doesn’t involve being a
deviant. However, if he knows the acts of deviance
of his neighbor, he will be more suspicious against
him and will denounce him.
This modelling is quite difficult to implement
and require a lot attention. For testing the model,
several configurations will be applied to multiple
simulations. Usually, these tasks take a lot of time to
prepare. Not to waste time, the creation of these
initial states should be automated.
3.1.3 MASC with SIEGMAS
In this case study, we are trying to model the
interactions between stakeholders in a precise
geographical area. To do so we have to create a
representation of a region in a simulation platform.
In this specific example, the region of Analamanga
(Madagascar) which directly usable map data are
quite difficult to find, is used. So we go from a map
extracted from a digital document that was provided
to us (Figure 5).
Figure 5: Analamanga region map.
Without MASC, we would have been constraint
to crisscross the image in software image processing
and then to manually select and assess the color of
each sector of the grid. Thanks to MASC, these tasks
were simply handled by giving the image file, the
number of sectors to cut in the width direction and a
color swatches that we simply took from the legend
of the map by clicking on it. Afterwards, a preview
was displayed to us (Figure 6). We decided then to
prioritize the colors of the sectors or not and
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