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Last modified: 08 Mar 2016 11:42

Course Overview

Computational Intelligence covers a wide range of issues that developed in parallel with, or in competition to, symbolic AI. The major constituents of the field are bio-inspired computing – which deals with an ever expanding number of biologically related techniques – and fuzzy logic – which deals with reasoning under conditions of vagueness. In this course we will explore a number of topics that are core to Computational Intelligence (e.g. neural nets and evolutionary computing) and these will lead into some state-of-the-art approaches (such as fuzzy model-based reasoning and learning).​

Course Details

Study Type Undergraduate Level 4
Session First Sub Session Credit Points 10 credits (5 ECTS credits)
Campus Old Aberdeen Sustained Study No
  • Professor George Coghill

What courses & programmes must have been taken before this course?

  • Any Undergraduate Programme (Studied)

What other courses must be taken with this course?


What courses cannot be taken with this course?


Are there a limited number of places available?


Course Description

A selection of topics spanning a range of Computational Intelligence approaches under the following headings:

  • Fuzzy Systems (e.g. Fuzzy Logic, Fuzzy Rule Bases, Mamdani Methods).
  • Model-based Technology (e.g. Qualitative and Fuzzy Qualitative reasoning, model-based diagnosis).
  • Nature Inspired Computing (eg. Neural Nets Artificial Immune Systems, Particle Swarm optimisation methods. This will include a rudimentary presentation of the basic biological principles involved).​

Degree Programmes for which this Course is Prescribed


Contact Teaching Time

Sorry, we don't have that information available.

Teaching Breakdown


1st Attempt

  • In-course assessment.
  • Final exam.


  • One 2-hour examination (100%).

Formative Assessment



​Formative feedback for in-course assessments will be provided in written form. Additionally, formative feedback on performance will be provided informally during practical sessions.

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