Option IA - Logique et IA Symbolique
2018 - 2019
- Objective of the course:
- Providing the bases of symbolic artificial intelligence.
- Detailing a few selected advanced topics.
- Acquiring skills 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, Protegé and fuzzyDL.
- Prerequisite: Basic knowledge in computer sciences and algebra.
- Course content:
- 1 - Introduction - Reminder on bases on logics (syntax, semantics...) and overview of several logics (propositional, first order, modal...) - Isabelle Bloch
- 2,3 - Description logics, fuzzy logics, ontologies and Knowledge Graphs - Natalia Diaz
- 4 - Symbolic learning: formal concept analysis, decision trees - Isabelle Bloch
- 5 - Tutorial on ontology engineering and design. Building your own ontologies using (Fuzzy) OWL, Protegé and fuzzyDL for real life knowledge graph problems- (practical work, including a report at the end of the course) - Natalia Diaz
- 6,7 - Some typical examples in AI: revision, merging, abduction, with illustrations on preference modeling and image understanding - Isabelle Bloch
- 8 - Written exam
- written exam (50%) - Authorized document: 2 A4 sheets (4 pages) of notes you will have prepared in advance
- reports handed in after the practical work, which will require to create a couple of ontologies as part of a decision support system of a freely elected domain problem (50%)
- Course material (regularly updated):
Contact: Isabelle Bloch -- Natalia Diaz Rodriguez