Unit information: Evolutionary Computing in 2011/12

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Unit name Evolutionary Computing
Unit code COMSM0302
Credit points 10
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Burgess
Open unit status Not open
Pre-requisites

None

Co-requisites

EMAT31600

School/department Department of Computer Science
Faculty Faculty of Engineering

Description including Unit Aims

This unit describes the basic theory, mechanisms and techniques of evolutionary computing. It covers genetic algorithms, genetic programming and artificial life, with an emphasis on the use of such techniques in machine learning. Practical, hands-on experiments are conducted by the students. This unit is aimed at MSc students following the Machine Learning and Data Mining theme.

Aims:

The aim of this unit is to equip you with the knowledge and skills necessary to apply evolutionary computing techniques to the solution of complex optimisation and machine learning problems. The unit describes the basic theory, mechanisms and techniques of evolutionary computing. It covers genetic algorithms, genetic programming and other evolutionary computing techniques. The unit is aimed at MSc students following the Machine Learning and Data Mining theme, and fourth year undergraduates.

Assessment Information

Assessment is by coursework (50%) and exam (50%)

GA: Genetic Algorithm coursework - 30% - submission deadline 5th December 2008

GP: Genetic Programming coursework - 20% - submission deadline 12th December 2008

Exam: Theory exam - 50% - January 2009

Reading and References

Lecture notes are provided during the course, but the following are also excellent references.

An errata sheet (https://www.cs.bris.ac.uk/Teaching/Resources/COMSM0302/GaTheoryErrata.pdf) for Reeves and Rowe is available.

Reeves, C. R. and Rowe, J. E. Genetic Algorithms - Principles and Perspectives: A Guide to GA Theory. 2003. Kluwer Academic Publishers. ISBN: 1402072406 Price: £88.50 Recommended

Goldberg, D. E. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company. 1989. ISBN: 0201157675 Price: £56.99 Background

Mitchell, M. An Introduction to Genetic Algorithms 1998. MIT Press ISBN: 0262631857 Price: £21.95 Background