Last modified: 22 May 2019 17:07
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.
|Session||First Sub Session||Credit Points||15 credits (7.5 ECTS credits)|
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.
Information on contact teaching time is available from the course guide.
1st Attempt: 1 two-hour written examination (75%); continuous assessment (25%).
Resit: One 2-hour examination (100%).
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.