At the end of the course, the student will master the main concepts and techniques of Artificial Intelligence.
The objective of the course is to expose the basic concepts and techniques of Artificial Intelligence.
After an introduction to the field of Artificial Intelligence, the course is divided into two parts: (i) on the one hand, the study of the search techniques, and (ii) the study of knowledge representations. The first part deals with exhaustive search methods, heuristics as well as constraint solving. The second part studies procedural and declarative representations. It also covers the basics machine learning. Throughout the course, logic programming is used to write programs.
The student is evaluated on two bases: on the one hand on the submission of work to be done during the quadrimester and on the other hand on the basis of a written exam and an oral exam. Successful completion of the course is conditional to the successful completion of each of these parts.
As the work to be carried out requires a major involvement of the student during the whole semester, in application of article 32, paragraph 1 of the Regulations of Studies and Examinations, only work of sufficient quality (sanctioned by a mark higher than 5/20) will be allowed to be represented in the 2nd session.
S. Russel et P. Norvicq, Artificial Intelligence: a Modern Approach. Pearson, 2016.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Standard | 0 | 5 | ||
| Standard | 3 | 5 |