diff --git a/resources/EvA2.props b/resources/EvA2.props index 9b954cbd..d9800fe9 100644 --- a/resources/EvA2.props +++ b/resources/EvA2.props @@ -16,3 +16,6 @@ ModulePackage = eva2.server.modules # filter class for modules. Do not alter! ModuleFilterClass = eva2.server.modules.AbstractModuleAdapter + +# Full EvA2 version number +EvA2Version = 2.043 \ No newline at end of file diff --git a/resources/FitnessConvergenceTerminator.html b/resources/FitnessConvergenceTerminator.html index 7b82bfc5..099e963f 100644 --- a/resources/FitnessConvergenceTerminator.html +++ b/resources/FitnessConvergenceTerminator.html @@ -7,10 +7,13 @@

The fitness convergence terminator stops the optimization, when there has been hardly -any change in the best population fitness (within percentual or absolute distance) for a certain -time, given in generations or fitness calls.
+any change in the best fitness in the population (within percentual or absolute distance) for a certain +time, given in generations or fitness calls. In case of multi-objective optimization, the 2-norm of +the fitness vector is +currently used.
Be aware that, if the optimization is allowed to be non-monotonic, such as for (,)-ES strategies, and if the optimum is close to zero, it may happen that the fitness fluctuates due to numeric -issues and does not easily converge in a relative measure. +issues and does not easily converge in a relative way.
+Check the help for the PopulationMeasureTerminator for additional information. \ No newline at end of file diff --git a/resources/PhenotypeConvergenceTerminator.html b/resources/PhenotypeConvergenceTerminator.html index e38dcf97..cc4093e5 100644 --- a/resources/PhenotypeConvergenceTerminator.html +++ b/resources/PhenotypeConvergenceTerminator.html @@ -6,10 +6,11 @@

Phenotype Convergence Terminator


-The phenotype convergence terminator stops the optimization, when there has been hardly +The phenotype convergence terminator stops the optimization when there has been hardly any change in the best population individual (within percentual or absolute distance) for a certain time span, given in generations or fitness calls.
Be aware that, if the optimum individual is close to zero, it may happen that its phenotype values -fluctuate due to numeric issues and do not easily converge in a relative measure. +fluctuate due to numeric issues and do not easily converge in a relative measure.
+Additional information is given for the superclass PopulationMeasureTerminator. \ No newline at end of file diff --git a/resources/PopulationMeasureTerminator.html b/resources/PopulationMeasureTerminator.html new file mode 100644 index 00000000..25c3165a --- /dev/null +++ b/resources/PopulationMeasureTerminator.html @@ -0,0 +1,31 @@ + + +Population Measure Terminator + + +

Population Measure Terminator

+
+

+ An abstract class giving the framework for terminators based on + a population measure converging for a given time (number of evaluations or + generations). + The class detects changes of a population P using a measure m over time and may signal convergence + if the measure m(P) behaved in a certain way for a given time. Convergence may + be signaled + +The fitness convergence terminator stops the optimization, when there has been hardly +any change in the best fitness in the population (within percentual or absolute distance) for a certain +time, given in generations or fitness calls. In case of multi-objective optimization, the 2-norm of +the fitness vector is +currently used.
+Be aware that, if the optimization is allowed to be non-monotonic, such as for (,)-ES strategies, +and if the optimum is close to zero, it may happen that the fitness fluctuates due to numeric +issues and does not easily converge in a relative way.
+ + \ No newline at end of file