A Distributed Architecture for Multimodal Emotion Identificatio

Abstract

The paper is focused on the application of ABM to simulate the evolution of the agricultural system of the Grand Duchy of Luxembourg under the external shock of fostering the production of maize to be used for bio-methane generation. The modeling exercise is part of a larger scale effort, which aims at the evaluation of the potential environmental impacts arising from policy implementation, following the methodology known as Consequential Life Cycle Assessment (CLCA). The application of ABM brings from one side an additional level of complexity to the assessment, but it also allows a finer scale bottom-up modeling, allowing the simulation of aspects (such as behavioral components in farmers’ choices or adaptive social processes such as imitation) that was not possible to grasp from other (e.g. purely economically oriented) modeling perspectives. The ABM model implemented has as many agents as the inventoried farmers in Luxembourg are. Although the paper only presents preliminary results, it already allows exploring the influence of farmers’ environmental awareness on the environmental impacts linked to farming activities. This is possible thanks to the attribution to the agents’ profiles of one specific feature which simulates their “green consciousness level”.