# Multiagent Approach For The Representation Of Information In A Decision Support System

Fahem Kebair and Fr´ed´eric Serin Universit´e du Havre, LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Syst`emes, 25 rue Philippe Lebon, 76058, Le Havre Cedex, France
{fahem.kebair, frederic.serin}**@univ-lehavre.fr**
Abstract. **In an emergency situation, the actors need an assistance allowing them to react swiftly and efficiently. In this prospect, we present**
in this paper a decision support system that aims to prepare actors in a crisis situation thanks to a decision-making support. The **global architecture of this system is presented in the first part. Then we focus on a**
part of this system which is designed to represent the information of the current situation. This part is composed of a multiagent system that is made of factual agents. Each agent carries a semantic feature and aims to represent a partial part of a situation. The agents develop thanks to their interactions by comparing their semantic features using proximity measures and according to specific ontologies.

Keywords. **Decision support system, Factual agent, Indicators, Multiagent system, Proximity measure, Semantic feature.**

## 1 Introduction

Making a decision in a crisis situation is a complicated task. This is mainly due to the unpredictability and the rapid evolution of the environment state. Indeed, in a critic situation time and resources are limited. Our knowledge about the environment is incomplete and uncertain, verily obsolete. Consequently, it is difficult to act and to adapt to the hostile conditions of the world. This **makes** sense to the serious need of robust, dynamic and intelligent planning **system for** search-and-rescue operations to cope with the changing situation and to best save people [9]. The role of such a system is to provide an emergency planning that allows actors to react swiftly and efficiently to a crisis case.

In this context, our aim is to build a system designed to help decision-makers manage cases of crisis with an original representation of information. From the system point of view, detecting a crisis implies its representation, its **characterisation and its comparison permanently with other crisis stored in scenarios base.**
The result of this comparison is provided to the user as the answer of the global system .

The idea began with the speech interpretation of human actors during a crisis
[3], [5]. The goal was to build an information, and communication system (ICS)
arXiv:0803.3501v1 [cs.AI] 25 Mar 2008