Last modified: 28 Jun 2018 10:27
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.
Study Type | Undergraduate | Level | 3 |
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Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
Campus | None. | Sustained Study | No |
Co-ordinators |
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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%). Only marks obtained at first attempt can be used for Honours Classification.
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.
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