Descriptif
This course aims at providing the bases of symbolic AI, along with a few selected advanced topics.
It includes courses on formal logics, ontologies, symbolic learning, typical AI topics such as revision, merging, etc., with illustrations on preference modeling and image understanding.
Objectifs pédagogiques
At the end of the course students will be able to understand different kinds of logic families, formulate reasoning in such formal languages, and manipulate tools to represent knowledge and its adaptation to imprecise and incomplete domains through the use of OWL and Protegé.
Diplôme(s) concerné(s)
Format des notes
Numérique sur 20Littérale/grade européenPour les étudiants du diplôme Diplôme d'Ingénieur de l'Ecole Nationale Supérieure de Techniques Avancées
Le rattrapage est autorisé (Max entre les deux notes écrêté à une note seuil)- le rattrapage est obligatoire si :
- Note initiale < 6
- le rattrapage peut être demandé par l'étudiant si :
- 6 ≤ note initiale < 10
- Crédits ECTS acquis : 2 ECTS
Le coefficient de l'UE est : 1
La note obtenue rentre dans le calcul de votre GPA.
L'UE est évaluée par les étudiants.
Programme détaillé
Introduction - Reminder on logics (syntax, semantics...) and overview of several logics (propositional, first order, modal...)
Description logics, ontologies
Symbolic learning: formal concept analysis, decision trees
Tutorial on ontology engineering and design. Building your own ontologies using OWL and Protegé for real life problems- (practical work, including a report at the end of the course)
Some typical examples in AI: revision, merging, abduction, with illustrations on preference modeling and image understanding
