Intelligence artificielle

This course will introduce students to the fundamentals of artificial intelligence. Four themes will be covered:

• Search and Planning; addressing topics such as informed search, CSP and local search, games, and adversarial search.
• Probabilistic Reasoning; with an emphasis on Bayesian networks, their structure, and how to perform inferences.
• Decision Making Under Uncertainty; with topics such as Markov decision processes and reinforcement learning.
• Machine Learning: Which will be discussed in general, as well as several methods, such as the Naive Bayesian classifier and perceptrons.

With this course, students should have sufficient knowledge and technical skills to work on AI-related projects and succeed in AI-related courses in the ULB Master CS program and other universities.

Required and Corequired knowledge and skills

Programming, algorithmics and standard mathematics knowledge obtained in the first Bachelor year.

Required and corequired courses

Theoretical sessions (24 hours) and exercises (24 hours) and 2 hackathons

• The weekly theoretical session covers the course material.
• The weekly exercises allow students to solve problems related to each part of the course.
• During the year, two hackathons will be organized. These will allow students to demonstrate their ability to translate the concepts covered in class into a functional system.

References, bibliography, and recommended reading

This course is directly based on AI - a Modern Approach, 4th edition. There are both an English and French version of this book.  You can also get access to an online copy via this link.

the ULB library also has 4-5  copies of this book available.

 

Course notes

• Université virtuelle

Additional information

All information related to this course is available on UV.

Contacts

Tom.Lenaerts@ulb.be

Campus

Plaine

Method(s) of evaluation

• written examination
• Group work

written examination

Group work

• The exam in January covers the practical exercises portion of the course.
• During the year, two hackathons will be organized, in which teams of students will implement a solution to a problem, drawing on the knowledge acquired during the course

There is no second session for the hackathons; the grade obtained in this part will therefore be carried over to the second session.

Mark calculation method (including weighting of intermediary marks)

The course grade is composed of two parts:

• 40% of the total grade is based on the hackathons (3/20 of the total grade for the first hackathon and 5/20 for the second).
• 60% of the total grade is based on the written exam (12/20 of the total grade).

There is no second session for the hackathons; the grade obtained in this part will therefore be carried over to the second session.

Language(s) of evaluation

• french
• (if applicable english, Dutch )