2019-2020 / INFO0049-1

Knowledge representation


28h Th, 4h Pr, 50h Proj.

Number of credits

 Master of Science (MSc) in Data Science5 crédits 
 Master of Science (MSc) in Computer Science and Engineering5 crédits 
 Master of Science (MSc) in Computer Science and Engineering (double diplômation avec HEC)5 crédits 
 Master of Science (MSc) in Data Science and Engineering5 crédits 
 Master of Science (MSc) in Computer Science5 crédits 
 Master of Science (MSc) in Computer Science (double diplômation avec HEC)5 crédits 
 Master in mathematics (120 ECTS)6 crédits 
 Master in mathematics (60 ECTS)6 crédits 


Pascal Gribomont

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

Classically a program is a piece of procedural knowledge. Allowing a more declarative style is often useful in artificial intelligence and other areas. First order logic is introduced here as a declarative programming technique. PROLOG is viewed as a partial but convenient implementation of the principles of logic programming.

Learning outcomes of the learning unit

Basic principles of logic programming.
Basic programming techniques in Prolog.
Automated deduction in Prolog.
From functional programming to logic programming: code improvement and simplification.
Verification of program correctness with respect to their specifications.
Elementary applications in artificial intelligence (puzzles, riddles, one- or two-player games).

Prerequisite knowledge and skills

INFO0051-1 Logic and INFO0054-1 Functional Programming
A good theoretical and practical knowledge of mathematical logic and proficiency in functional programming are needed to take this course.

Planned learning activities and teaching methods

Prolog programming - exercises

Mode of delivery (face-to-face ; distance-learning)


Recommended or required readings

Slides are available.
Also useful:
P. Gochet et P. Gribomont, Logique, volume 3: Méthodes pour l'intelligence artificielle (chapitres 10, 11 et 12), Hermès, Paris, 2000.
L. Sterling and E. Shapiro, The Art of Prolog, MIT Press, 1994 (2nd ed).
I. Bratko, Prolog Programming for Artificial Intelligence, Prentice Hall, 2000 (3rd ed).

Assessment methods and criteria

Homeworks. Final examination.

Work placement(s)

Organizational remarks



Pascal Gribomont <gribomont@montefiore.ulg.ac.be>