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CS3025: KNOWLEDGE BASED SYSTEMS (2017-2018)

Last modified: 04 Jul 2017 10:12


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
Co-ordinators
  • Dr Adam Wyner
  • Dr Jeff Pan

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?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

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.

Degree Programmes for which this Course is Prescribed

  • BSc Computing Science and Philosophy
  • Bachelor Of Science In Business Mngmt & Information Systems
  • Computing Science Joint
  • Computing Science Minor
  • MA Information Systems and Management

Contact Teaching Time

76 hours

This is the total time spent in lectures, tutorials and other class teaching.

Teaching Breakdown


Assessment

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.

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.

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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