net.sourceforge.cilib.pso.dynamic.detectionstrategies.RandomSentryDetectionStrategy Maven / Gradle / Ivy

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A library of composable components enabling simpler Computational Intelligence
There is a newer version: 0.8
/**           __  __
 *    _____ _/ /_/ /_    Computational Intelligence Library (CIlib)
 *   / ___/ / / / __ \   (c) CIRG @ UP
 *  / /__/ / / / /_/ /   http://cilib.net
 *  \___/_/_/_/_.___/
 */
package net.sourceforge.cilib.pso.dynamic.detectionstrategies;


import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import net.sourceforge.cilib.algorithm.population.PopulationBasedAlgorithm;
import net.sourceforge.cilib.entity.Entity;
import net.sourceforge.cilib.entity.Topology;
import net.sourceforge.cilib.math.random.generator.Rand;
import net.sourceforge.cilib.pso.dynamic.DynamicParticle;
import net.sourceforge.cilib.pso.particle.Particle;

public class RandomSentryDetectionStrategy extends
        EnvironmentChangeDetectionStrategy {
    private static final long serialVersionUID = 6254159986113630555L;

    private int sentries;
    private double theta;
    private int[] sentryIDs;
    private boolean initialised = false;
    ArrayList sentryList;

    public RandomSentryDetectionStrategy() {
        sentries = 1;
        theta = 0.001;
    }

    public void Initialise(E algorithm){
        sentryIDs = new int[sentries];
        int populationSize = algorithm.getTopology().size();

        //randomly select the sentries among the particles
        for(int i=0; i topology = algorithm.getTopology();
        this.sentryList = new ArrayList();
        Iterator iterator = topology.iterator();

        int sentryCounter = 0;
        while (iterator.hasNext() && sentryCounter copy) {
        this.sentries = copy.sentries;
        this.theta = copy.theta;
    }

    public RandomSentryDetectionStrategy getClone() {
        return new RandomSentryDetectionStrategy(this);
    }

    /** Check for environment change:
     * Pick the specified number of random particles (sentries) and evaluate their current positions.
     * If the difference between the old fitness and the newly generated one is significant (exceeds a predefined theta)
     * for one or more of the sentry particles, assume that the environment has changed.
     * @param algorithm PSO algorithm that operates in a dynamic environment
     * @return true if any changes are detected, false otherwise
     */
    public boolean detect(E algorithm) {
        if(initialised == false){
            this.Initialise(algorithm);
        }
        boolean envChangeOccured = false;

        for (Particle nextSentry : sentryList) {
            double oldSentryFitness = nextSentry.getFitness().getValue();
            double newSentryFitness = algorithm.getOptimisationProblem().getFitness(nextSentry.getPosition()).getValue();

            if(Math.abs(oldSentryFitness - newSentryFitness) >=  theta) {
                envChangeOccured = true;
                break;
            }
        }
        return envChangeOccured;
    }

    /**
     * @return the sentries
     */
    public int getSentries() {
        return sentries;
    }

    /**
     * @param sentries the sentries to set
     */
    public void setSentries(int sentries) {
        this.sentries = sentries;
    }

    /**
     * @return the theta
     */
    public double getTheta() {
        return theta;
    }

    /**
     * @param theta the theta to set
     */
    public void setTheta(double theta) {
        this.theta = theta;
    }
}