COMP24412: Symbolic Artificial Intelligence
This course is being delived by Giles Reger, Andre Freitas, and Joe Razavi.
Please see the
School syllabus page for other information.
Aims and objectives
The aim of this course is to provide the conceptual and practical
(systems building) foundations for knowledge representation and
reasoning in Artificial Intelligence.
A student completing this course unit should be able to:
- Describe, differentiate and apply different knowledge
representation formalisms for modelling knowledge bases.
- Explain how these formalisms affect the reasoning process.
- Write Prolog programs to solve automated reasoning tasks and
explain how they will execute
- Apply, demonstrate and program knowledge-based learning
- Apply, demonstrate and program formal models for natural
language processing in the context of semantic parsing and
natural logic inference.
- 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
- Explain the theoretical limitations of automated theorem
Lecture and Lab notes and materials will be available from Blackboard for the first half of the course and from here for the second half.
As per School policy, we will not be providing hard copies of
- Weeks 1-2 (Andre) - Knowledge Representation
- Weeks 3-4 (Joe) - Prolog
- Weeks 5-6 (Andre) - Parsing
- Weeks 7-10 (Giles) - Automated Reasoning
- Week 11 (Andre) - Abduction and ILP
- Week 12 - Revision
This has been updated in an attempt to clarify things. The work is the same but we have changed how it is described
There are 3 coursework exercises to be completed over 5 lab sessions.
Labs are assessed offline (there is no face-to-face marking). See SPOT for deadlines.
There are three Blackboard quizzes in weeks 5, 7, and 10.
- Parsing. This is split into two parts
- Part 1 is on Natural Language and Representation and should be done in Lab session 1
- Part 2 is on Parsing and should be done in Lab session 3
- Prolog. This should be done in Lab session 2 and is due before Coursework 1
- Reasoning. This is split into two parts to be done in Lab sessions 4 and 5
- Stuart Russell and Peter Norvig, Artificial Intelligence: A
Modern Approach, Global Edition, 2016.
- Patrick Blackburn, Johan Bos and Kristina Striegnitz: Learn Prolog Now!,
College Publications, 2006.
- Sebastian Loebner, Understanding Semantics, Second Edition,
- Dennis Merritt, Building Expert Systems in Prolog.
Please note that the course has changed considerably this in
2018/19 and previous exams should be treated with care - they
are not indicative of content or style.
Check out the following sites: