diff --git a/eo/tutorial/html/eoCheckPoint.html b/eo/tutorial/html/eoCheckPoint.html index 9ac0ec7f..49dd8d99 100644 --- a/eo/tutorial/html/eoCheckPoint.html +++ b/eo/tutorial/html/eoCheckPoint.html @@ -2,7 +2,7 @@ - + Variation Operators @@ -23,7 +23,12 @@ continuators - Checkpoints - CheckPointing What is Checkpointing about? -
Evolutionary Algorithms are ticked +
Evolutionary Algorithms are almost all timely ticked, the basic time +unit being what is called a generation. EO checkpointing mechanism allow +you to program things that you want to be done at the end of every generation. +This includes deciding to stop, outputing some statistics on the current +state of the algorithm,  updating some dynamical variables of your +algorithm, saving the population to disk, ...

EO classes described in this page:


  @@ -48,7 +54,8 @@ means that the algorithm stops only when the continuator returns Interface:  The abstract class for computing stopping conditions is eoContinue, and the interface for its operator() is -

                            +

                           + bool operator()(const eoPop<EOT>& )

which you could have guessed from the inheritance @@ -79,15 +86,16 @@ passed at construct time. Don't forget to returnfalseis met! Existing continuators: -Of course you can find out all existing (non-virtual!) subclasses -of eoContinue by looking at its  inheritance +Of +course you can find out all existing (non-virtual!) subclasses of eoContinue +by looking at its  inheritance diagram. But you might find it more convenient to have them listed here:

- +


Combining continuators: @@ -101,8 +109,8 @@ boolean result as an eoContinue.

Writing a checkpoint:
This is something you should never have to do. However, should you -fell you have to do it, please do - and send us both the reasons that lead -you to that (wqhat is it you couldn't do with existing eoCheckPoint), and +feel you have to do it, please do - and send us both the reasons that lead +you to that (what is it you couldn't do with existing eoCheckPoint), and the resulting code, of course.

Statistics: diff --git a/eo/tutorial/html/eoLesson4.html b/eo/tutorial/html/eoLesson4.html index 627cb24c..b56f18cb 100644 --- a/eo/tutorial/html/eoLesson4.html +++ b/eo/tutorial/html/eoLesson4.html @@ -2,7 +2,7 @@ - + Tutorial: Lesson 3 @@ -24,32 +24,40 @@ this time you will have full control of all components< from the command-line or a parameter file. You can even use the algorithm decribed here without any other knowledge of EO, just by writing your fitness function as a plain C++ function. This -is why this lesson starts with a user's guide, +is why this lesson starts with a user's guide, most of it being representation-independent, with some parts that are specific of respectively the binary and the real algorithms.
However, the ultimate purpose of this tutorial is to be able to do your own experiments - and these these will likely fall outside the scope -of these two programs. This is why you should also read the programmer's -guides, as the structure and memory managements are here radically different -that in the 3 previous lessons - though relying of course on the same objects. +of these two programs. This is why you should also read the programmer's +guides, as the structure and memory managements are here radically +different that in the 3 previous lessons - though relying of course on +the same objects.
 


User's -guide -
As already said, the behavior of the algorithms +guide +

As already said, the behavior of the algorithms will be exactly the same as the previous one as far as optimization is concerned. Only now you will be able to tune every component of the algorithms -- except the type of genotype - using run-time parameters. +(except the type of genotype) using run-time parameters.
Also, as in previous lessons, most of the code is representation-independent, i.e. is the same for both the binary genotypes and the real-valued genotypes. This small user's guide reflects that, but you can go directly to the binary or the real -parts if you wish. Parameters input The way to input parameters has already -be described in Lesson 3. To get -a list of parameters, type the command with option --help (or -h): with -both testBit and testReal this will result in +parts if you wish. +

Warning: this +is a user guide, not a programming guide. In particular, the keywords +of the parameters are not +the names of +the underlying classes (though they should be similar in most cases). +

User's guide: +Parameter input The way to input parameters +has already be described in Lesson +3. To get a list of parameters, type the command with option --help +(or -h): with both testBit and testReal this will result in

-User's guide: -The status file +User's guide:The +status file
This file will always contain the list of the parameters that have been actually used by the last run of the program, however thay have been entered (try testBit -G1 and take a look a the status file). The parameters that are commented out (a # character comments -out the rest of the line) in the file were not specified by the user. -

User's guide: -Representation-independent parameters -
The parameters are organized in sections. -
The first section only contains the random seed. -

###### General ###### +out the rest of the line) in the file are those that were not specified +by the user. +

User's guide:Representation-independent +parameters +
The parameters are organized in sections. In +what follows, the fixed font colored text is directly taken from the status +file and is commented between the lines. +
+

+
Section ###### +General ######
# --help=0 # -h : Prints this message -
Whether or not help was requested is handled -through a boolean parameter -
# --seed=988700289 # -S -: Random number seed -
The seed for the Random -Number Generator -

###### Output ###### +
Boolean parameter of +absolutely no interest: tells whether or not help was requested. +

# --seed=988700289 # -S : +Random number seed +
Unsigned long parameter: +the seed for the Random Number Generator +If the parameter is absent, then time(0) is used, which indicates the number +of seconds since Jan. 1 1980, is used ... and stored in the status file, +of course, so you can repeat the same run by simply assigning that value +again. There is no default value ("true" random +seed). +
+

+
Section ###### +Output ######
This section contains parameters related to output -(to screen, to files, graphical, ...). -
# --useEval=1 # Use nb of +(to screen, to files, graphical, ...). +

# --useEval=1 # Use nb of eval. as counter (vs nb of gen.) -
Boolean parameter, whether or not you want the -nb of evluations to be displayed and used as counter in plots -
# --printBestStat=1 # Print +
Boolean parameter: +whether or not you want the nb of evluations to be displayed and used as +counter in statistics outputs and plots. Default +is true. +

# --printBestStat=1 # Print Best/avg/stdev every gen. -
Boolean parameter, toggles screen output of indicated -statistics -
# --plotBestStat=0 # Plot +
Boolean parameter: +toggles screen output of indicated statistics. Default +is true. +

# --plotBestStat=0 # Plot Best/avg Stat -
Boolean parameter, toggles gnuplot output of -best and average plots (Linux only at the moment) -
# --BestFileName=best.xg +
Boolean parameter: +toggles gnuplot output of best and average plots (Linux only at the moment). +Default is false. +

# --BestFileName=best.xg # Name of file for Best/avg/stdev -
String parameter, if present, the statistics -are stored in that file (no default) -
# --printPop=0 # Print sorted +
String parameter: +if present, the statistics are stored in that file (no +default) +

# --printPop=0 # Print sorted pop. every gen. -
Boolean parameter, adds a dump of the whole population -to the screen every generation -
# --printFDC=1 # Print FDC +
Boolean parameter: +adds a dump of the whole population to the screen every generation. Is +likely to generate huge +output! Default is false. +

# --printFDC=1 # Print FDC coeff. every gen. -
Boolean parameter, adds Fitness Distance Correlation -to output every generation -
# --plotFDCStat=0 # Plot +
Boolean parameter: +adds Fitness Distance Correlation to output every generation. Default +is false. +

# --plotFDCStat=0 # Plot FDC scatter plot -
Boolean parameter, toggles the Fitness Distance -Correlation plot (Fitness vs distance to best) -
# --plotHisto=0 # Plot histogram +
Boolean parameter: +toggles the Fitness Distance Correlation plot (Fitness vs distance to best). +Default is false. +

# --plotHisto=0 # Plot histogram of fitnesses -
Boolean parameter: if on, gnuplot is used to -plot the sorted population (fitness vs rank). Gives a graphical idea of -the diversity. -

###### Persistence ###### +
Boolean parameter: +if on, gnuplot is used to plot the sorted population (fitness vs rank). +Gives a graphical idea of the diversity. Default +is false. +
+

+
Section ###### +Persistence ######
This section contains parameters handling job -restart -
# --Load= # -L : A save -file to restart from -
String parameter: if present, the initial population -(and the RNG status) is read from indicated file. That file must +dump and restart mechanism +

# --Load= # -L : A save file +to restart from +
String parameter: +if present, the initial population (and the RNG) is read from indicated +file. That file must come from a previous save (or must be in same format!), i.e. must contain a popualtion, the RNG and all parameters. If no other parameter is modified, using a previously saved population and RNG will give exactly the same @@ -130,89 +165,143 @@ results than having run that previous run longer. And a way to be sure to re-use the same parameters is to ... use that very save file as parameter file, as it contains all actual parameters in the right format.
Note that if not enough individuals are read, -the remaining are randomly initialized. No default value. -
# --recomputeFitness=0 # +the remaining are randomly initialized. No +default value. +

# --recomputeFitness=0 # -r : Recompute the fitness after re-loading the pop.? -
Boolean parameter: in case some individuals are -read from a file, their fitness is read too. If this one is true, it is -nevertheless recomputed. -
# --saveFrequency=0 # Save +
Boolean parameter: +in case some individuals are read from a file, their fitness is read too. +If this one is true, it is nevertheless recomputed. Default +is false i.e. use fitnes that's in the file. +

# --saveFrequency=0 # Save every F generation (0 = only final state, absent = never) -
Integer parameter: interval between two dump -to disk of the whole population (+RNG + parameters) to disk, in a file -named genNN.sav, where NN is the generation number. If this prameter -is present (even with 0 or negative value), the final population will always -be saved, whatever the reason for stopping. Hence the only way to avoid -all saves is to omit the parameter (there is no default value). -
# --saveTimeInterval=0 # +
Integer parameter: +interval between two dump to disk of the whole population (+RNG + parameters) +to disk, in a file named genNN.sav, where NN is the generation number. +If this prameter is present (even with 0 or negative value), the final +population will always be saved, whatever the reason for stopping. Hence +the only way to avoid all saves is to omit the parameter (there is no +default value). +

# --saveTimeInterval=0 # Save every T seconds (0 or absent = never) -
Integer parameter: time interval between two -population (+RNG + parameters) dumps to disks. Files are names timeNN.sav. -See pervious parameter description for ore details. No default value. -
# --status=t-eoGA.status +
Integer parameter: +time interval between two population (+RNG + parameters) dumps to disks. +Files are names timeNN.sav. See pervious parameter description for ore +details. No default value. +

# --status=t-eoGA.status # Status file -
String parameter: name of the status file (that -contains all parameters in the input format). There is no way to avoid -creating that file except recompiling ... or giving the name /dev/null -(Unix). -

###### Stopping criterion -###### +
String parameter: +name of the status file (that contains all parameters in the input format). +There is no way to avoid creating that file except recompiling ... or giving +the name /dev/null (Unix). Default value is ProgramName.status +
+

+
Section ###### +Stopping criterion ######
This section allows to decide when the algorithm -will stop. -
# --maxGen=100 # -G : Maximum +will stop. +

# --maxGen=100 # -G : Maximum number of generations (0 = none)
Integer parameter: maximum number of generations. -Default is 0 which is equivalent to infinity. -
# --steadyGen=100 # -s : +A value of 0 disables that stopping criterion. Default +is 100. +

# --steadyGen=100 # -s : Number of generations with no improvement -
Integer parameter: stops whenever that number -of generations is passed without any improvement of the best fitness in -the population, provided the following minimum number of generations has -been done. No default value. -
# --minGen=0 # -g : Minimum +
Integer parameter: +stops whenever that number of generations is passed without any improvement +of the best fitness in the population, provided the following minimum number +of generations has been done. No default value. +

# --minGen=0 # -g : Minimum number of generations
Integer parameter: the above steadyGen parameter starts its job only after that minimum nuber of generations is passed. -No default value. -
# --maxEval=0 # -E : Maximum +No default value. +

# --maxEval=0 # -E : Maximum number of evaluations (0 = none)
Integer parameter: maximum number of generations. -No default value. -
# --targetFitness=0 # -T +No default value. +

# --targetFitness=0 # -T : Stop when fitness reaches
Real-valued parameter: the algorithm stops whenever -the best fitness reaches that target. No default value. -
# --CtrlC=0 # -C : Terminate +the best fitness reaches that target. No default +value. +

# --CtrlC=0 # -C : Terminate current generation upon Ctrl C
Boolean parameter: if true, Ctrl C only stops after the current generation as completed (eventually dumping population -to a file if some saver is active). -

###### engine ###### +to a file if some saver is active). THis very useful feature is only available +in Unix at the moment. Default is false. +
+

+
Section ###### +engine ######
In this section, one chooses all components of -the Evolution Engine (selection, replacemenet and the like). -
# --selection=DetTour(2) +the Evolution Engine (selection, replacemenet +and the like). +

# --selection=DetTour(2) # -S : Selection: Roulette, DetTour(T), StochTour(t) or Sequential(ordered/unordered) -
String parameter: Name of selection procedure. -Availabable are the roulette wheel +
String parameter: +Name of selection procedure. Availabable +are the roulette wheel (name Roulette, -fitness scaling coming soon), deterministic +fitness scaling coming soon); deterministic tournament (name DetTour with size - integer > 2 - in parentheses right after the name, use double -quotes on the command line),  stochastic tournament (name StochTour -with probability - float in [0.5, 1] - in parentheses), sequential (name +quotes on the command line);  stochastic +tournament (name StochTour +with probability - float in [0.5, 1] - in parentheses); sequential +(name Sequential, all individuals in turn), either from best to worst (option ordered -in parentheses), or in random ordered (option unordered) -or finally repeated independent uniform choices  (name Random). -
# --offspringRate=100% # --O : Nb of offspring (percentage or absolute) +in parentheses), or in random ordered (option unordered); +and finally repeated independent uniform +choices  (name Random). +Default is DetTour(2). +

# --nbOffspring=100% # -O +: Nb of offspring (percentage or absolute) +
Integer or real-valued parameter: +this parameter indicates the amount of +offspring that will be generated from +the genitors every generation. However, this amount can be specified either +relative to the +population size, and it should then end with percent character (%), or +as an absolute +integer number (without the percent char). +
Indeed, you can either want, say 7 times more +offspring than parents (a rather common situation in Evolution Strategies), +in which case you give value 700% to nbOffspring +parameter; or you might want a single offspring whatever the population +size, like in Steady-State evolution engines, in which case you simply +enter value 1. Default is 100%.

# --replacement=Comma # -R -: Replacement: Comma, Plus or EPTour(T) -
String parameter: Name of replacement procedure. -Availabable are -
# --weakElitism=0 # -w : +: Replacement: Comma, Plus, EPTour(T), SSGAWorst, SSGADet(T), SSGAStoch(t) +
String parameter: +Name of replacement procedure. Availabable are the ES +plus and comma deterministic replacement +strategies (named respectively Plus +and  Comma); +EP stochastic tournament +(name EPTour +with tournament size in parentheses); and the steady-state +replacement procedures, at the moment +only based on fitnesses, replacement being either deterministic +(new born replace worst parent, name SSGAWorst),  +or based on a tournament  (name SSGADet +for deterministic tournament, size in parentheses, and SSGAStoch  +for stochastic tournament, probability in parentheses). Default +is Comma (which btw is also SGA generational +replacement whenever there are as many offspring +as parents). +

# --weakElitism=0 # -w : Old best parent replaces new worst offspring *if necessary* -
  +
Boolean parameter: +if true, weak elitism is added to the replacement procedure (i.e. if the +best fitness among the offspring is less than the best fitness, the best +parent replaces the worst offspring). Default +is false. +

User's guide: +Bistring specific parameters +
 


Programmer's diff --git a/eo/tutorial/html/eoTutorial.html b/eo/tutorial/html/eoTutorial.html index 3a3a0bee..38e87a92 100644 --- a/eo/tutorial/html/eoTutorial.html +++ b/eo/tutorial/html/eoTutorial.html @@ -17,9 +17,9 @@ and to

EO Tutorial

-
Version 0.95 - May. 2 2001
-New: Lesson4 - with user guide of fully operational program -
+
Version 0.95 - May. 2 2001 +
New: Lesson4 +- with user guide of fully operational program

Welcome to EO tutorial/on-line documentation.

Please note that this tutorial is not supposed