COMP24412: Symbolic Artificial Intelligence

Aims and objectives

A student completing this course unit should 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.

Structure

Lecture and Lab notes and materials will be available from here. As per School policy, we will not be providing hard copies of notes.

The following table is the main reference for what is going on in the course and will be updated frequently throughout the course as further details are given.

The suggested reading will be mainly taken from Artificial Intelligence: A Modern Approach (Third Edition) referenced as AIAMA. It should be noted that this is suggested only and not examinable (only lectured material is examinable).

Reading

Exams

Please note that the course has changed considerably this year and previous exams should be treated with care. Further guidance will be added here later.

• General examinations material
• Exams information specifically for students
• Exams feedback