This course is run at the The University of Nottingham within the School of Computer Science & IT. The course is run by Graham Kendall (EMAIL : gxk@cs.nott.ac.uk)
If you want a gentle introduction to GA's, as well as some history of the people involved (particularly John Holland), you might want to see (Levy, 1993).
This section is presented as follows.
Firstly, an overview of GA's is given. Following this the GA algorithm is presented.
Next the three main parts of a GA are discussed; these being the evaluation
module, the population module and the reproduction module.
And finally a list of references is
presented that the interested student might find useful. The books I have listed
are considered to be the "standard" textbooks for GA's. In addition,
the references I make throughout this part of the course are all listed on that
page.
Please note, that this section is largely based on (Davis, 1991), as I find
this gives a more complete description than (Russell, 1995), which is the book
I use for a lot of my AI course. I also find that (Davis, 1991) is very easy
to read and is a very good introductory book to the subject.
Another good introduction is chapter 1 of (Goldberg, 1989). You might also like to look at (Michalewicz, 1996), (Michalewicz, 2000) and (Mitchell, 1996) which are also "standard" GA textbooks.
You should also read the follwoing paper - Genetic Algorithms for the Operations Researcher (Reeves C. Genetic Algorithms for the Operations Researcher, INFORMS Journal of Computing, 1997, Vol 9(3), pp 231-250)
I also recommend that you access other resources on the internet, as there is lots of information about genetic algorithms.
Try this Google Search, for starters
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Last Updated : 25/01/2002