diff --git a/eo/tutorial/html/eoLesson1.html b/eo/tutorial/html/eoLesson1.html index f9116bdf0..22a09acbe 100644 --- a/eo/tutorial/html/eoLesson1.html +++ b/eo/tutorial/html/eoLesson1.html @@ -33,19 +33,22 @@ follow the guided tour. Later you will be asked to

-I want to run an Evolutionary Algorithm + +
I want to run +an Evolutionary Algorithm now

You can choose to run a standard bitstring Genetic Algorithm (as defined in Goldberg's book) or a standard real-valued @@ -74,12 +77,16 @@ one individual per line, its fitness first, then the number of items (bits or real numbers) of the genotype, and the genotype itself. The final population hopefully contains the solution in the discrete case, and is close to it in the continuous case. -

You need now to take a look at either programs -by browsing alone through the  sources for FirstBitGA -and FirstRealGA, or follow the guided tour -below, or go directly to the exercises. +
+

Browsing +the code: +

Now you need to take a look at the program codes, either by browsing +alone through the  sources for FirstBitGA +and FirstRealGA, or by following the guided +tour below. You might prefer to go directly to the exercises.

-Browsing the code:

+ +
Guided tour:

-Exercise 1: maximize your -own function

+ +
Exercise +1: maximize your own function This is very easy - if your search space is that of bitstring or of unbounded real numbers.

-Exercise 2: check the differences between both programs

+ +
Exercise +2: check the differences between both programs Go and take a look at the code for these programs (Bit - Real). Use the symbolic representation of an Evolutionary Algorithm (you should understand that figure now, otherwise @@ -337,9 +347,10 @@ part of the EA is coded. Try to spot the differences between both codes: there are not so many!
After you've tried that alone, take a look at the solution :-) -
 

-Exercise 3: change the selection procedure

+ +
Exercise +3: change the selection procedure This is rather straightforward ... if you know what other types of selection are available!
At the moment, let's only consider only the following simple ones: @@ -368,7 +379,8 @@ select; Note that all these classes of eoObjects are derived from the abstract class eoSelectOne. -

Lessons: +

+

Lessons learned: @@ -67,7 +67,9 @@ argument is a vector<bool> or a Note: Also, +
  +

  +

Note: Also, a non-templatized fitness can be compiled separately (not done here) into an object file once and for all (remember @@ -84,6 +86,8 @@ requires.
 

  +
  +
 

Note: In the previous files (Bit - Real) , the last 2 types were deduced from the first (2nd argument = fitness @@ -107,7 +111,9 @@ You can also use different initializers and call them in turn through the call to pop.append() function (see Exercise 2). -


Note: Don't +
  +

  +

Note: Don't forget to evaluate the population: the eoPop has no idea of the eval function, so it has to be done from outside!!!