INFO0049-1

Duration

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

Number of credits

	Master of Science (MSc) in Data Science	5 crédits
	Master of Science (MSc) in Computer Science and Engineering	5 crédits
	Master of Science (MSc) in Computer Science and Engineering (double diplômation avec HEC)	5 crédits
	Master of Science (MSc) in Data Science and Engineering	5 crédits
	Master of Science (MSc) in Computer Science	5 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

Lecturer

Pascal Gribomont

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester

Schedule

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, hybrid learning)

Face-to-face.

Organisational adjustments related to the current health context

. . . .

Assessment methods and criteria

Below you will find information on the evaluation methods planned for in-person and remote exams as well as those planned for hybrid sessions. Depending on how the health crisis evolves, the chosen method will be communicated to you no later than one month before the start of the exam session.

Homeworks. Final examination.

Work placement(s)

Organizational remarks

http://www.montefiore.ulg.ac.be/~gribomon/cours/cours.html

Contacts

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

Knowledge representation