/*
* File name: SelectionTournament.java (package eas.users.lukas.neuroCEGPM.selection)
* Author(s): Lukas König
* Java version: 7.0
* Generation date: 04.03.2014 (09:26:09)
*
* (c) This file and the EAS (Easy Agent Simulation) framework containing it
* is protected by Creative Commons by-nc-sa license. Any altered or
* further developed versions of this file have to meet the agreements
* stated by the license conditions.
*
* In a nutshell
* -------------
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*
* Under the following conditions:
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* - Share Alike -- If you alter, transform, or build upon this work, you may
* distribute the resulting work only under the same or a similar license to
* this one.
*
* + Detailed license conditions (Germany):
* http://creativecommons.org/licenses/by-nc-sa/3.0/de/
* + Detailed license conditions (unported):
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package eas.users.lukas.neuroCEGPM.selection;
import java.math.BigDecimal;
import java.util.HashSet;
import java.util.LinkedList;
import java.util.List;
import java.util.Random;
import eas.miscellaneous.StaticMethods;
import eas.users.lukas.neuroCEGPM.RobNeural;
/**
* @author Lukas König
*/
public class SelectionTournament implements Selection {
private static final long serialVersionUID = 1462365765040422087L;
private int tournamentSize = 3;
private Random rand;
public SelectionTournament(Random rand) {
this.rand = rand;
}
@Override
public void select(List<RobNeural> population) {
HashSet<RobNeural> visited = new HashSet<RobNeural>();
LinkedList<RobNeural> tournament;
while (visited.size() <= population.size() - tournamentSize) {
tournament = new LinkedList<RobNeural>();
RobNeural bestRob = null;
double bestFit = Double.NEGATIVE_INFINITY;
while (tournament.size() < tournamentSize) {
RobNeural rob = population.get(rand.nextInt(population.size()));
if (!visited.contains(rob)) {
tournament.add(rob);
visited.add(rob);
if (rob.getFitness() > bestFit) {
bestFit = rob.getFitness();
bestRob = rob;
}
}
}
LinkedList<Thread> threads = new LinkedList<Thread>();
for (RobNeural rob : tournament) {
LinkedList<BigDecimal> genomeTrans = null;
if (bestRob.getGenomeTrans() != null) {
genomeTrans = new LinkedList<>(bestRob.getGenomeTrans());
}
threads.add(rob.setController(
new LinkedList<BigDecimal>(bestRob.getGenome()),
genomeTrans,
bestRob.getRand(),
true));
}
StaticMethods.joinThreads(threads);
for (RobNeural rob : tournament) {
rob.setFitness(bestRob.getFitness());
}
}
}
}