logo EDITE Karim EL MERNISSI
Identité
Karim EL MERNISSI
État académique
Soutenance prévue le 2017-12-13
Sujet: Une étude de la génération d'explication dans un système à base de règles
Direction de thèse:
Encadrement de thèse:
Laboratoire:
Voisinage
Ellipse bleue: doctorant, ellipse jaune: docteur, rectangle vert: permanent, rectangle jaune: HDR. Trait vert: encadrant de thèse, trait bleu: directeur de thèse, pointillé: jury d'évaluation à mi-parcours ou jury de thèse.
Productions scientifiques
oai:hal.archives-ouvertes.fr:hal-01615522
Introducing Causality in Business Rule-Based Decisions
International audience
Decision automation is expanding as many corporations capture and operate their business policies through business rules. Because laws and corporate regulations require transparency, decision automation must also provide some explanation capabilities. Most rule engines provide information about the rules that are executed, but rarely give an explanation about why those rules executed without degrading their performance. A need exists for a human readable decision trace that explains why decisions are made. This paper proposes a first approach to introduce causality to describe the existing (and sometimes hidden) relations in a decision trace of a Business Rule-Based System (BRBS). This involves a static analysis of the business rules and the construction of causal models.
Advances in Artificial Intelligence: From Theory to Practice: 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, Arras, France, June 27-30, 2017, Proceedings, Part I IEA/AIE 2017 - 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems https://hal.archives-ouvertes.fr/hal-01615522 IEA/AIE 2017 - 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, Jun 2017, Arras, France. Springer, Advances in Artificial Intelligence: From Theory to Practice: 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, Arras, France, June 27-30, 2017, Proceedings, Part I, 10350, pp.433-439, Lecture Notes in Computer Science. 〈10.1007/978-3-319-60042-0_47〉ARRAY(0x7f54725a8188) 2017-06-27
Soutenance
Thèse: Une étude de la génération d'explication dans un sytème à bases de règles
Soutenance:
Rapporteurs: Vincent MOUSSEAU    Alexis TSOUKIAS