COMP24412 Symbolic AI syllabus 2019-2020
22 in total, 2 per week
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 (24 hours)
- Practical classes & workshops (10 hours)
- Analytical skills
- Problem solving
On successful completion of this unit, a student will be able to:
- Describe the syntax and semantics of first-order logic and use it to model problems
- Apply reasoning techniques (transformation to clausal form, resolution, saturation) to establish properties of first-order problems
- Explain the theoretical limitations of automated theorem provers
- Write Prolog programs to solve automated reasoning tasks and explain how they will execute
- Describe, differentiate and apply different knowledge representation formalisms for modelling knowledge bases.
- Explain how these formalisms affect the reasoning process.
- Apply, demonstrate and program knowledge-based learning methods.
- Apply, demonstrate and program formal models for natural language processing in the context of semantic parsing and natural logic inference.
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.