The subject of this thesis is the development of a Knowledge-Based System for situations of crisis. Two main research issues have been studied during the development of the system : knowledge acquisition and knowledge validation. The knowledge acquisition part integrates both knowledge acquisition and machine learning techniques. As a fust step, the knowledge acquisition methods have been used to identify the descriptive and strategie domain knowledge and to construct the description language to use for defining the examples needed for the machine learning. The second step is to use a machine learning technique to incrementally construct a knowledge graph using cases on interventions in situations of crisis obtained from the domain experts. Two different procedures are proposed for the exploitation phase of the system. The first procedure is the interactive use of the knowledge graph, while the second procedure is the deductive use of the knowledge graph. The knowledge validation approach proposed is based on the interactive use of the knowledge graph and on a follow-up on expert interventions in situations of crisis.
