Assignment Title
Name & student no.
1 INTRODUCTION
Concise description of task asked and your
approach(es).
mutation rate or population size. Show example
solutions. Try different operators from the lectures or
wider literature.
Results from the worksheets should not be included.
2 BACKGROUND RESEARCH
Use clear referencing and avoid including material
directly unless carefully indicated as from another
source. Half to a whole page expected.
For the very keen, it would be great to see
comparative performance on either benchmark
optimisation problems/data or algorithms. You don
need to implement other algorithms, use of Weka,
etc. is fine.
3 EXPERIMENTATION
4 CONCLUSIONS
Describe your basic algorithm so anyone who knows
about basic EAs could hopefully repeat what you
have done. Describe the representation, the
parameters, the fitness calculation, etc.
Concise summary of what you found and learned.
Identification of ways you might do things
differently next time, and why.
REFERENCES
Present your results as averaged behaviour over
more than one run, eg (graph not of assignment):
Author, A. (1970) The best way to do AI ever. IEEE
Transactions on Data Mining 1(1): 209-238.
Source code as an appendix
Figure Example: Initial performance.
Show the effects of varying parameters and give
potential
explanations
as
to
why
the
behaviour/performance changes. Eg vary the

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