Kaced, Doryan and Mejean, Romain and Richa, Aurélien and Gaudou, Benoît
and Saqalli, Mehdi
PASHAMAMA: an agricultural process-driven agent-based model of the Ecuadorian Amazon.
(2019)
In: 19th International Workshop on Multi-Agent-Based Simulation, part of the Federated AI Meeting (MABS 2018), 14 July 2018 (Stockholm, Sweden).
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(Document in English)
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Official URL: https://doi.org/10.1007/978-3-030-22270-3_5
Abstract
This article presents the PASHAMAMA model that aims at studying the situation in the northern part of the Amazonian region of Ecuador in which the intensive oil extraction has induced a high rise of population, pollution, agricultural work and deforestation. It simulates these dynamics impacts on both environment and population by examining exposure and demography over time thanks to a retro-prospective and spatially explicit agent-based approach. Based on a previous work that has introduced roads, immigration and pollution (induced by the oil industry) dynamics, we focus here on the agricultural and the oil salaried work sides of the model. Unlike many models that are highly focused on the use of quantitative data, we choose a process-based approach and rest on qualitative data extracted from interviews with the local population: farmers are not represented by highly cognitive agents, but only attempt to fulfill their local objectives by fulfilling sequentially their constraints (e.g. eating before earning money). We also introduce a new evaluation method based on satellite pictures that compares simulated to “real” data on a thematic division of the environment.
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