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:

Structure

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 notes.

Lectures

Labs

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.
  1. Parsing. This is split into two parts
  2. Prolog. This should be done in Lab session 2 and is due before Coursework 1
  3. Reasoning. This is split into two parts to be done in Lab sessions 4 and 5
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.

Suggested Reading

Exams

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.

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