Last modified: 25 Sep 2019 09:58
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 | Aberdeen | Sustained Study | No |
| Co-ordinators |
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Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 75 | |
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| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
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| Assessment Type | Summative | Weighting | 25 | |
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| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Formative feedback for in-course assessments will be provided in written form. Additionally, formative feedback on performance will be provided informally during practical sessions. |
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| Knowledge Level | Thinking Skill | Outcome |
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There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
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| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
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| Knowledge Level | Thinking Skill | Outcome |
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