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Unit information: Computational Logic for Artificial Intelligence in 2021/22

Unit name Computational Logic for Artificial Intelligence
Unit code COMSM0022
Credit points 10
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Professor. Peter Flach
Open unit status Not open




School/department Department of Computer Science
Faculty Faculty of Engineering

Description including Unit Aims

This unit provides an introduction to knowledge-driven AI from the perspective of computational logic. It covers the basic principles of knowledge representation and automated inference by means of logic programming languages, which have pattern matching and backtracking search as primitive operations.

This then leads to more advanced methods in natural language processing and machine learning which exploit the representation and reasoning power of logic programming.

Intended Learning Outcomes

Upon successful completion of this unit students will be able to:

  1. Understand the main techniques for intelligent reasoning and learning using logic-based knowledge representation.
  2. Implement and apply these techniques to solve practical problems by means of the declarative programming language Prolog.

Teaching Information

Teaching will be delivered through a series of mostly synchronous sessions, including lectures, seminars, practical activities, discussion groups and self-directed exercises.

Assessment Information

1 Summative Assessment, 100% - Coursework. This will assess all ILOs.


If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. COMSM0022).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.