EO Tutorial

About this tutorial

• Algorithm-Based means you start from a very simple, ready-to-run algorithm, and gradually modify it, making it both more powerful and more complex.
• Component-Based means you start by examining the components of an EA one by one, down to the level of complexity you feel comfortable with, and then build the whole algorithm using those components you need (or the one you are mastering). Such approach might be viewed as going through a simplified user guide, too.

Related documents

• There are of course a few (very few) programming hints that you should know.
• THe EO documentation - automatically generated from the comments in the code - is very helpful, to get an idea of the inheritance diagrams of EO classes, and to quickly reach some specific part of the code.

The top page of each class documentation is for instance the inheritance diagram of the class, and you'll learn a lot by simply looking at it.
• And, last but not least, we assume you know approximately that an Evolutionary Algorithm looks like this, but otherwise you can try this very brief introduction).

Colors and navigation:

You will see this diagram in quite many places, as for instance at the top of all examples - usually it will be clicable and will help you navigate among the different parts of an EO program. See the brief introduction to Evolutionary Computation for a detailed explanation.

But in the text itself, colors are important, as they will be used throughout this tutorial to clearly mark which part of the algorithm we are discussing. So please keep in mind that, whereas orange is for emphasis,

• Yellowish is for representation, i.e. the choice of the genotype
• Magenta is for the stochastic operators that are representation-dependent, i.e. initialisation and variation operators (crossover, mutation and the like).
• Green is for the implementation of Darwinism, i.e. the way the individuals are selected for reproduction and survive.
• Red is for evaluation, i.e. the computation of the fitness of all individuals
• Blue is for interactions of the user and the program, as for instance choice of stopping criterion, on-line display of nice statistics or initial choice of all program parameters.
• Brown is for everything that is NOT part of any of the above, i.e. random number generator, or basic C++/STL syntax .
• Note that pink will be used to desctibe the syntax of compile orders (i.e. at the oepratoring system level, see e.g. below).
• Last, but not least, all links into EO documentation will use the Helvetica typeface, like this line you are now reading.

• an interface that would allow you to build your Evolutionary Programs by a few clics; such a thing does exist, is called EASEA, and is complementary to this tutorial as it helps the user to build some simple EO programs from simple description. But there are things that EASEA cannot do, and you will have to do it yourself and will need to imcrease your knowledge about EO for that.

Before you start

(myname@myhost) EOdir/Tutorial %

so you should now type in

make lesson1

and see something like

(myname@myhost) EOdir/Tutorial % make lesson1
c++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -c FirstBitGA.cpp
c++ -Wall -g -o FirstBitGA FirstBitGA.o ../../src/libeo.a ../../src/utils/libeoutils.a
c++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -c FirstRealGA.cpp
c++ -Wall -g -o FirstRealGA FirstRealGA.o ../../src/libeo.a ../../src/utils/libeoutils.a

and two now executable files should have appeared in the subdirectory Lesson1, namely FirstBitGA and FirstRealGA (see First lesson to know more about these two ready-to-run programs). If this doesn't work, please go back to the main EO directory and run the installation program.

You should also test that you can access the EO documentation in the menu line below: you might not need to go there immediately, but just in case you make rapid progress ... This menu bar should be on all pages of this tutorial, allowing you to navigate easily.

Last, but not least: EO is improving only  from the good will of contributors. This is also true for this tutorial: If you find anything that you think could be improved, you are welcome to e-mail me.