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.
Private Study Hours: 128
Contact Hours: 22
Total Hours: 150
Main assessment methods:
Take-home computer test (about 15 hours) (20%)
One short essay (about 1,000 words) (20%)
Examination (60%)
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)
On successfully completing the Level 6 module students will be able to:
1. 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. 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. 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. exploit library and online resources to support investigations into these areas.
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