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1 CRESTIC - Centre de Recherche en Sciences et Technologies de l-Information et de la Communication 2 URCA - Université de Reims Champagne-Ardenne

Abstract : Crisis management challenges decision support systems designers. One problem in the decision marking is to develop systems able to help the coordination of the different involved teams. Another challenge is to make the system work with a degraded communication infrastructure. Each workstation or embedded application must be able to help to make a decision with a degraded network by taking into account the potential decisions made by other agents. We propose in this article a multi-agent model, based on an ant colony optimization, and designed to manage the complexity in the deployment of resources to solve a crisis. This model is able to manage data uncertainty, and its global goal is to optimize, in a stable way, fitness functions, like saving lives, defined by multiple users. Moreover, thanks to a reflexive process, the model is able to manage the effects into the environment of its decisions, in order to take more appropriate decisions. Thanks to our transactional model, the system is also able to take into account a large data amount without exploring all potential solutions. The graphical interface should be able to make the user defining rules database. Then, if the nature of the crisis is deeply unchanged, users should be able to change rules- databases.

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Keywords : Crisis Management combinatorial optimization Mutli-agent systems Ant Based Colony Optimization Decision Making Decision Making Under Uncertainty Uncertainty Quantification Big Data

Mots-clés : Gestion de crise Optimisation Combinatoire Systèmes Multi-Agents Optimisation par colonie de fourmis Aide à la décision Incertitude





Author: Jason Mahdjoub - Francis Rousseaux -

Source: https://hal.archives-ouvertes.fr/



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