Skip to Content


Last modified: 22 May 2019 17:07

Course Overview

Knowledge Representation (KR) is concerned with how knowledge can be represented symbolically and manipulated in an automated way by reasoning programs. In fact, KR has long been considered central to AI because it is a significant factor in determining the success of knowledge-based systems.

This course describes the formalisation of knowledge and its use in knowledge-based systems. It follows the whole "life-cycle" of knowledge, from the initial identification of relevant expertise, through its capture, representation (in ontology and /or rule languages), use (based on reasoning), evaluation, and reuse.

Course Details

Study Type Undergraduate Level 3
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus None. Sustained Study No
  • Dr Jeff Pan
  • Professor George Coghill

Qualification Prerequisites

  • Either Programme Level 3 or Programme Level 4

What courses & programmes must have been taken before this course?

What other courses must be taken with this course?


What courses cannot be taken with this course?


Are there a limited number of places available?


Course Description

  • Knowledge representation: propositional logic, description logics, ontology, rules, uncertainty and vagueness.
  • Knowledge reasoning: description logics-based and rule-based systems, tableaux (completion) algorithm for description logics, forward chaining and backward chaining for rules.
  • Knowledge engineering: expertise identification, capture, evaluations, reusability.

Further Information & Notes

Assistive technologies may be required for any student who is unable to use a standard keyboard/mouse/computer monitor. Any students wishing to discuss this further should contact the School Disability Co-ordinator. (ii) Non-graduating students would require the following background/experience: familiarity with a procedural programming language.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers

Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

1st Attempt: 1 two-hour written examination (75%); continuous assessment (25%).

Resit: One 2-hour examination (100%).

Formative Assessment

During lectures, the Personal Response System and/or other ways of student interaction will be used for formative assessment. Additionally, practical sessions will provide students with practice opportunities and formative assessment.


Formative feedback for in-course assessments will be provided in written form. Additionally, formative feedback on performance will be provided informally during practical sessions.

Course Learning Outcomes


Compatibility Mode

We have detected that you are have compatibility mode enabled or are using an old version of Internet Explorer. You either need to switch off compatibility mode for this site or upgrade your browser.