Lectures for INFO8006 Introduction to Artificial Intelligence, ULiège, Fall 2025.
- Instructor: Gilles Louppe
- Teaching assistants: Gérôme Andry, Fanny Bodart
- When: Fall 2025, Thursday 8:30 AM to 12:30 AM
- Classroom: B28/Mania Pavella
- Contact: info8006@montefiore.ulg.ac.be
- Discord: https://discord.gg/Y8UP2SBu2h
- Office: I87b (Gérôme and Fanny), Thursday 12:30 AM to 3 PM
| Date | Topic |
|---|---|
| September 18 | Course syllabus [PDF] Lecture 0: Introduction to artificial intelligence [PDF] Lecture 1: Intelligent agents [PDF] |
| September 25 | Lecture 2: Solving problems by searching [PDF] Tutorial: Project 0, Project 0 bis |
| October 2 | Lecture 3: Games and adversarial search [PDF] Exercises 1: Solving problems by searching [PDF] [Solutions] |
| October 9 | Lecture 4: Quantifying uncertainty [PDF] Lecture 5: Probabilistic reasoning [PDF] Exercises 2: Games and adversarial search [PDF] [Solutions] |
| October 16 | Lecture 5: Probabilistic reasoning (continued) [PDF] Lecture 6: Reasoning over time [PDF] Exercises 3: Quantifying uncertainty [PDF] [Solutions] |
| October 23 | Lecture 6: Reasoning over time [PDF] (continued) Exercises 4: Probabilistic reasoning [PDF] [Solutions] |
| October 30 | No class |
| November 6 | Lecture 6: Reasoning over time [PDF] (continued) Lecture 7: Machine learning and neural networks [PDF] Exercises 5: Reasoning over time [PDF] [Solutions] |
| November 13 | Lecture 7: Machine learning and neural networks (continued) [PDF] Exercises 5: Reasoning over time (continued) [notebook] [Solutions] |
| November 16 | Deadline for Project 1 |
| November 20 | Lecture 7: Machine learning and neural networks (continued) [PDF] Exercises 6: Machine learning [PDF] [Solutions] |
| November 27 | Lecture 8: Making decisions [PDF] Exercises 6: Machine learning [PDF] (continued) [Solutions] |
| December 4 | Lecture 9: Reinforcement Learning [PDF] Exercises 7: Making decisions & RL [PDF] |
| December 11 | No lecture Exercises 7: Making decisions & RL [PDF] (continued) Exercises 8: Past exam |
| December 14 | Deadline for Project 2 |
| December 18 | No lecture |
- General instructions
- Python tutorial [video (Linux), video (Windows)]
- Part 0: (tutorial session in class)
- Part 1: Bayes Filter (due by November 16)
- Part 2: Imitation Learning (due by December 14)
- January 2019 (solutions)
- August 2019
- January 2020
- August 2020 (solutions)
- January 2021 (solutions)
- August 2021
- January 2022 (solutions)
- August 2022
- January 2023 (solutions)
- August 2023
- January 2024
- August 2024
- January 2025
- August 2025
Materials covered by the exam are listed here.
Due to progress in the field, some of the lectures have become less relevant. However, they are still available for those who are interested.
| Topic |
|---|
| Lecture: Constraint satisfaction problems [PDF] |
| Lecture: Inference in Bayesian networks [PDF] |
| Lecture: Communication [PDF] |
| Lecture: Artificial general intelligence and beyond [PDF] |