Natural Computation - COMP8370

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2021 to 2022
Autumn Term 7 15 (7.5) Alex Freitas checkmark-circle


There is an increasing use of nature-inspired computational techniques in computer science. These include the use of biology as a source of inspiration for solving computational problems, such as developments in evolutionary algorithms and swarm intelligence. It is therefore proposed to allow students the opportunity to become exposed to these types of methods for use in their late careers.


Contact hours

Total contact hours: 22
Private study hours: 128
Total study hours: 150

Method of assessment

Main assessment methods
60% Examination, 40% Coursework

Indicative reading

Eiben, AE, Smith, JE. (2015) Introduction to Evolutionary Computing, 2nd Edition. Springer.
Dorigo, M. and Stutzle, T. (2004) Ant Colony Optimization, MIT Press.
Barnes, DJ, Chu, D. (2010) Introduction to Modeling for Biosciences, Springer

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
1 To be able to describe what is meant by a natural computation paradigm, list a number of natural computing paradigms and give a brief description of each together with
some examples of their (actual or potential) applications.
2 To be able to select the appropriate technique for a particular problem from a set of problem-solving heuristics based on these natural computing paradigms, and to be
able to justify this choice based on a knowledge of the properties and potential of these methods. To be able to compare the general capabilities of a number of such
methods and give an overview of their comparative strengths and weaknesses.
3 To be able to analyse phenomena from the natural world from the point of view of their being computational systems. To be able to take these phenomena and distinguish
between the features which are important for computational problem solving and those that are merely a fact of their realization in the natural world.
4 To be able to implement a natural computation system on the computer, and apply this program to the solution of problems.
5 To be able to exploit library and online resources to support investigations into these areas.


  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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