Study programme 2021-2022Français
Knowledge representation and reasoning
Programme component of Master's in Computer Science à la Faculty of Science

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-SCINFO-500-MOptional UEWIJSEN JefS832 - Systèmes d'information
  • WIJSEN Jef

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Anglais
Anglais, Français303000066.002nd term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-INFO-027Knowledge representation and reasoning3030000Q2100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Manage large-scale software development projects.
    • Apply, mobilise, articulate and promote the knowledge and skills acquired in order to help lead and complete a project.
    • Lead a project by mastering its complexity and taking into account the objectives, allocated resources and constraints that characterise it.
    • Demonstrate independence and their ability to work alone or in teams.
  • Manage research, development and innovation.
    • Organise and lead a research, development or innovation project to completion.
  • Master communication techniques.
    • Communicate, both orally and in writing, their findings, original proposals, knowledge and underlying principles, in a clear, structured and justified manner.
    • Where possible, communicate in a foreign language.
  • Develop and integrate a high degree of autonomy.
    • Aquire new knowledge independently.
    • Pursue further training and develop new skills independently.
    • Develop and integrate a high degree of autonomy to evolve in new contexts.
  • Apply scientific methodology.
    • Critically reflect on the impact of IT in general, and on the contribution to projects.
    • Demonstrate thoroughness, independence, creativity, intellectual honesty, and ethical values.

Learning Outcomes of UE

Knowledge Representation & Reasoning (KR&R) is a branch of Artificial Intelligence which uses logic languages for (a) representing information and knowledge, and (b) automatic reasoning on top of these representations. In this course, students will get acquainted with some recent technologies developed in the domain of KR&R, and will develop competencies that enable them to represent and solve computational problems by using the most appropriate logic formalism for the problem at hand. 

Content of UE

This course will focus on the following two applications of KR&R in particular:
(1) KR&R as the engine driving the Semantic Web, which is based on the formalism of Description Logic (DL) and implemented in the  W3C Web Ontology Language (OWL).
(2) KR&R for representing and solving problems in the complexity class NP (including all NP-complete problems). This application is based on the formalism known as Answer Set Programming (ASP).

Prior Experience

Students should be familiar with the foundations of propostional and first-order logic (which are taught, for example, in the courses Bases de Données I and II).

Type of Assessment for UE in Q2

  • Presentation and/or works
  • Written examination

Q2 UE Assessment Comments

The weight of the personal assignment can vary between 50% and 100% of the final mark; the weight that is most favorable to the student will be applied.

Type of Assessment for UE in Q3

  • Presentation and/or works
  • Written examination

Q3 UE Assessment Comments

The weight of the personal assignment can vary between 50% and 100% of the final mark; the weight that is most favorable to the student will be applied.

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
S-INFO-027
  • Cours magistraux
  • Conférences
  • Travaux pratiques

Mode of delivery

AAMode of delivery
S-INFO-027
  • Face to face

Required Reading

AA
S-INFO-027

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-INFO-027Web site with course notes and slides.
Free software.
Scientific articles.

Recommended Reading

AA
S-INFO-027

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-INFO-027Not applicable

Other Recommended Reading

AAOther Recommended Reading
S-INFO-027Not applicable

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
S-INFO-027Unauthorized
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 17/09/2021
20, place du Parc, B7000 Mons - Belgique
Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be