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Changed InterfaceMutationGenerational to InterfaceAdaptOperatorGenerational

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This commit is contained in:
Marcel Kronfeld 2011-03-14 13:58:49 +00:00
parent 215eeea57b
commit 767ada2371
8 changed files with 17 additions and 17 deletions
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2
src/eva2/server/go/individuals/InterfaceDataTypeBinary.java
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@ -3,7 +3,7 @@ package eva2.server.go.individuals;
import java.util.BitSet;
/** This interface gives access to a binary phenotype and except
* for problemspecific operators should only be used by the
* for problem specific operators should only be used by the
* optimization problem.
* Created by IntelliJ IDEA.
* User: streiche

2
src/eva2/server/go/individuals/InterfaceGAIndividual.java
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@ -3,7 +3,7 @@ package eva2.server.go.individuals;
import java.util.BitSet;
/** This interface gives access to a binary genotype and should
* only be used by mutation and crossover operators. Onyl exception are
* only be used by mutation and crossover operators. Exceptions are
* data type specific optimization strategies like CHC or PBIL.
* Created by IntelliJ IDEA.
* User: streiche

2
src/eva2/server/go/operators/mutation/InterfaceMutationGenerational.java → src/eva2/server/go/operators/mutation/InterfaceAdaptOperatorGenerational.java
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@ -10,7 +10,7 @@ import eva2.server.go.populations.Population;
* @author mkron
*
*/
public interface InterfaceMutationGenerational extends InterfaceMutation {
public interface InterfaceAdaptOperatorGenerational {
/**
* Perform adaption of the operator based on the selection performed by an EA.

4
src/eva2/server/go/operators/mutation/MutateESCovarianceMatrixAdaptionPlus.java
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@ -7,8 +7,8 @@ import eva2.server.go.problems.InterfaceOptimizationProblem;
import eva2.tools.math.Jama.Matrix;
public class MutateESCovarianceMatrixAdaptionPlus extends
MutateESCovarianceMatrixAdaption implements
InterfaceMutationGenerational {
MutateESCovarianceMatrixAdaption implements InterfaceMutation,
InterfaceAdaptOperatorGenerational {
protected double m_psuccess;
protected double m_cp;
protected double m_psuccesstarget = 0.44;

2
src/eva2/server/go/operators/mutation/MutateESRankMuCMA.java
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@ -243,7 +243,7 @@ class CMAParamSet implements InterfacePopulationChangedEventListener, Serializab
* @author mkron
*
*/
public class MutateESRankMuCMA implements InterfaceMutationGenerational, Serializable {
public class MutateESRankMuCMA implements InterfaceMutation, InterfaceAdaptOperatorGenerational, Serializable {
// int dim;
private double c_c, expRandStepLen;

2
src/eva2/server/go/operators/mutation/MutateESSuccessRule.java
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@ -14,7 +14,7 @@ import eva2.tools.math.RNG;
* Time: 14:11:49
* To change this template use File | Settings | File Templates.
*/
public class MutateESSuccessRule extends MutateESFixedStepSize implements InterfaceMutationGenerational, java.io.Serializable {
public class MutateESSuccessRule extends MutateESFixedStepSize implements InterfaceMutation, InterfaceAdaptOperatorGenerational, java.io.Serializable {
// it would be quite nice to make this variable static, but in that case
// no one could runs n independent ES runs in parallel anymore *sigh*
// protected static double m_MutationStepSize = 0.2;

10
src/eva2/server/go/strategies/EvolutionStrategies.java
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@ -4,7 +4,7 @@ import eva2.gui.BeanInspector;
import eva2.gui.GenericObjectEditor;
import eva2.server.go.InterfacePopulationChangedEventListener;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.operators.mutation.InterfaceMutationGenerational;
import eva2.server.go.operators.mutation.InterfaceAdaptOperatorGenerational;
import eva2.server.go.operators.mutation.MutateESSuccessRule;
import eva2.server.go.operators.selection.InterfaceSelection;
import eva2.server.go.operators.selection.SelectBestIndividuals;
@ -157,10 +157,10 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
this.evaluatePopulation(result);
if (result.getEAIndividual(0).getMutationOperator() instanceof InterfaceMutationGenerational) {
if (result.getEAIndividual(0).getMutationOperator() instanceof InterfaceAdaptOperatorGenerational) {
// this seems to be the right moment for the 1/5-success rule
// parents and result have the same size and correspond per individual
((InterfaceMutationGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptGenerational(fromPopulation, parents, result, m_UsePlusStrategy);
((InterfaceAdaptOperatorGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptGenerational(fromPopulation, parents, result, m_UsePlusStrategy);
}
return result;
@ -214,8 +214,8 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
// System.out.println("-- selected avg fit " + BeanInspector.toString(parents.getMeanFitness()) + " from last gen " + BeanInspector.toString(m_Population.getMeanFitness()));
// m_Population / parents are of sizes lambda / mu
if (parents.getEAIndividual(0).getMutationOperator() instanceof InterfaceMutationGenerational) {
((InterfaceMutationGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptAfterSelection(getPopulation(), parents);
if (parents.getEAIndividual(0).getMutationOperator() instanceof InterfaceAdaptOperatorGenerational) {
((InterfaceAdaptOperatorGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptAfterSelection(getPopulation(), parents);
}
// now generate the lambda offsprings

10
src/eva2/server/go/strategies/GeneticAlgorithm.java
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@ -2,7 +2,7 @@ package eva2.server.go.strategies;
import eva2.server.go.InterfacePopulationChangedEventListener;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.operators.mutation.InterfaceMutationGenerational;
import eva2.server.go.operators.mutation.InterfaceAdaptOperatorGenerational;
import eva2.server.go.operators.selection.InterfaceSelection;
import eva2.server.go.operators.selection.SelectRandom;
import eva2.server.go.operators.selection.SelectXProbRouletteWheel;
@ -115,8 +115,8 @@ public class GeneticAlgorithm implements InterfaceOptimizer, java.io.Serializabl
// System.out.println("Parents:"+parents.getStringRepresentation());
// double[] meas = parents.getPopulationMeasures();
if (parents.getEAIndividual(0).getMutationOperator() instanceof InterfaceMutationGenerational) {
((InterfaceMutationGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptAfterSelection(m_Population, parents);
if (parents.getEAIndividual(0).getMutationOperator() instanceof InterfaceAdaptOperatorGenerational) {
((InterfaceAdaptOperatorGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptAfterSelection(m_Population, parents);
}
for (int i = 0; i < parents.size(); i++) {
@ -133,8 +133,8 @@ public class GeneticAlgorithm implements InterfaceOptimizer, java.io.Serializabl
}
this.evaluatePopulation(result);
if (parents.getEAIndividual(0).getMutationOperator() instanceof InterfaceMutationGenerational) {
((InterfaceMutationGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptGenerational(m_Population, parents, result, true);
if (parents.getEAIndividual(0).getMutationOperator() instanceof InterfaceAdaptOperatorGenerational) {
((InterfaceAdaptOperatorGenerational)parents.getEAIndividual(0).getMutationOperator()).adaptGenerational(m_Population, parents, result, true);
}
return result;
}