 | Study programme 2023-2024 | Français | |
| Artificial Intelligence and graphs | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| S-INFO-021 |
|
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 20 | 10 | 0 | 0 | 0 | Q1 |
Content of Learning Activity
This course presents the links between Artificial Intelligence and Graph Theory, and this in both directions: how are graphs useful in AI? And what can AI do for graph theory? The topics covered will be related to constraint programming, approximation algorithms and computer-assisted discovery in graph theory, which is the main research topic of the Algorithms Lab of UMONS.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Russel, S. and Norvig, P., Artificial Intelligence: A Modern Approach, 3ième édition, Pearson, 2010 Williamson, Shmoys, The Design of Approximation Algorithms, Cambridge University Press (2011). Electronic version available online: www.designofapproxalgs.com
Mode of delivery
- Face-to-face
Type of Teaching Activity/Activities
- Cours magistraux
- Exercices dirigés
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)
Location of learning activity
- Université de Mons - Mons
Location of assessment
- Université de Mons - Mons