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  6. CS5044: Computational Intelligence

CS5044: COMPUTATIONAL INTELLIGENCE (2014-2015)

Last modified: 28 Jun 2018 10:27


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 Postgraduate Level 5
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus None. Sustained Study No
Co-ordinators
  • Professor George Coghill

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

None.

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

A selection of topics spanning a range off Computational Intelligence approaches under the following headings: - Fuzzy systems (e.g. Fuzzy Logice, Fuzzy Rule Bases, Mamdani Methods) - Model-based technology (e.g. Qualitative and Fuzzy Qualitative reasoning, model-based diagnosis) - Nature Inspired Computing (e.g. Neural Nets Artificial Immune Systems, Partcile Swarm optimisation methods. This will include a rudimentary presentation of the basic biological principles involved).

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

1 two hour written examination (75%); continuous assessment (25%).

Formative Assessment

There are no assessments for this course.

Feedback

None.

Course Learning Outcomes

None.
 

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