Introduction
I have been interested in artificial intelligence and artificial life for years
and I read most of the popular books printed on the subject. I developed a grasp
of most of the topics yet neural networks always seemed to elude me. Sure, I
could explain their architecture but as to how they actually worked and how they
were implemented… well that was a complete mystery to me, as much magic as
science. I bought several books on the subject but every single one attacked the
subject from a very mathematical and academic viewpoint and very few even gave any practical uses or examples. So for a long
long time I scratched my head and hoped that one day I would be able to
understand enough to experiment with them myself.
That day arrived some time later when - sat in a tent in the highlands
of
Scotland reading a book - I had a sudden blast of insight. It was one of
those
fantastic “eureka” moments and although Scotland is a beautiful place I
couldn’t wait to get to a computer so I could try out what I’d just
learnt. To my surprise the first neural net I programmed worked
perfectly and I
haven’t looked back since. I still have a great deal to learn, neural
nets are a
huge subject, but I hope I can share enough knowledge and enthusiasm to
get you
started on your own little projects. In many ways the fields of AI and
A-Life are
very exciting to work in. I think of these subjects as the explorers of
old must
have looked at all those vast empty spaces on the maps. There is so much
to learn and
discover.
I’ll start off by describing what a neural net actually is and what it’s
architecture is, then I’ll do a little theory on how we get it to perform for us
but I’ll try to use as little maths as possible. (Having some understanding of
mathematics is impossible to avoid however and the deeper you get into this
topic the more mathematics you are going to have to learn). Finally, we’ll get
to the fun bit. I’ll come up with a little project I will program and take you
through one step at a time. It will be in this last phase of the tutorial where
I hope you get the same “eureka” feeling for neural nets as I did back in rainy
old Scotland. Until then just sit back, absorb and be patient.
The C++ source
code for the tutorial and a pre-compiled executable can be found
here.
Update: A reader,
Sam Corder, has converted the
code into VB NET. You can download his source and executable
here.
Update: A reader,
Chris Reitzel, has converted the
code into DELPHI. You can download his source and executable
here.
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