COMP24412 Knowledge Based AI syllabus 2021-2022
11, 1 x per week
Lecture Video material
10 hours in total, 5 2-hour sessions.
Feedback methodsThe course has a number of lab exercises which are marked in the lab as usual, and feedback on these exercises is provided by written comments on the work and orally by the marker.
- Assessment written exam (2 hours)
- Lectures (22 hours)
- Practical classes & workshops (10 hours)
- Analytical skills
- Problem solving
On successful completion of this unit, a student will be able to:
- ILO 1 Describe, differentiate and apply different knowledge representation formalisms for modelling knowledge bases
- ILO 2 Describe the syntax and semantics of first-order logic (and the Datalog and Prolog fragments) and use it to model problems
- ILO 3 Demonstrate the forward and backward chaining reasoning methods and compare their implementation and practical characteristics (e.g. efficiency, termination)
- ILO 4 Apply resolution-based reasoning techniques (transformation to clausal form, resolution, saturation) to establish properties of first-order problems
- ILO 5 Explain the theoretical limitations of reasoning techniques for (fragments and extensions of) first-order logic
- ILO 6 Write Prolog programs to solve automated reasoning tasks and explain how they will execute
- ILO 7 Differentiate between deductive, inductive and abductive reasoning and apply them to perform learning and inference in knowledge based systems
- ILO 8 Relate knowledge based approaches to real world applications such as (but not limited to) program synthesis or circuit design verification
No reading list found for COMP24412.
Course unit materials
Links to course unit teaching materials can be found on the School of Computer Science website for current students.