//
// PRIVATE METHODS
//
private BayesNet createBurglaryNetwork()
{
BayesNetNode burglary = new BayesNetNode("Burglary");
BayesNetNode earthquake = new BayesNetNode("EarthQuake");
BayesNetNode alarm = new BayesNetNode("Alarm");
BayesNetNode johnCalls = new BayesNetNode("JohnCalls");
BayesNetNode maryCalls = new BayesNetNode("MaryCalls");
alarm.influencedBy(burglary, earthquake);
johnCalls.influencedBy(alarm);
maryCalls.influencedBy(alarm);
burglary.setProbability(true, 0.001);// TODO behaviour changes if
// root node
earthquake.setProbability(true, 0.002);
alarm.setProbability(true, true, 0.95);
alarm.setProbability(true, false, 0.94);
alarm.setProbability(false, true, 0.29);
alarm.setProbability(false, false, 0.001);
johnCalls.setProbability(true, 0.90);
johnCalls.setProbability(false, 0.05);
maryCalls.setProbability(true, 0.70);
maryCalls.setProbability(false, 0.01);
BayesNet net = new BayesNet(burglary, earthquake);
return net;
}
private static double enumerateAll(BayesNet net, List <string> unprocessedVariables,
Dictionary <String, bool> evidenceVariables)
{
if (unprocessedVariables.Count == 0)
{
return(1.0);
}
else
{
String Y = (String)unprocessedVariables[0];
if (evidenceVariables.ContainsKey(Y))
{
double probYGivenParents = net.probabilityOf(Y,
evidenceVariables[Y], evidenceVariables);
double secondTerm = enumerateAll(net, Util
.rest(unprocessedVariables), evidenceVariables);
return(probYGivenParents * secondTerm);
}
else
{
double sigma = 0.0;
Dictionary <String, bool> clone1 = cloneEvidenceVariables(evidenceVariables);
clone1.Add(Y, true);
double probYTrueGivenParents = net.probabilityOf(Y,
true, clone1);
double secondTerm = enumerateAll(net, Util
.rest(unprocessedVariables), clone1);
double trueProbabilityY = probYTrueGivenParents * secondTerm;
Dictionary <String, bool> clone2 = cloneEvidenceVariables(evidenceVariables);
clone2.Add(Y, false);
double probYFalseGivenParents = net.probabilityOf(Y,
false, clone2);
secondTerm = enumerateAll(net, Util.rest(unprocessedVariables),
clone2);
double falseProbabilityY = probYFalseGivenParents * secondTerm;
// System.Console.Write(secondTerm + " ) )");
sigma = trueProbabilityY + falseProbabilityY;
return(sigma);
}
}
}
public static double[] ask(Query q, BayesNet net)
{
Dictionary <String, bool> evidenceVariables = q.getEvidenceVariables();
double[] probDist = new double[2];
// true probability
evidenceVariables[q.getQueryVariable()] = true;
probDist[0] = enumerateAll(net, net.getVariables(), evidenceVariables);
// false probability
evidenceVariables[q.getQueryVariable()] = false;
probDist[1] = enumerateAll(net, net.getVariables(), evidenceVariables);
// System.Console.WriteLine( probDist[0] + " " + probDist[1]);
// return probDist;
double[] normalized = Util.normalize(probDist);
// System.Console.WriteLine( normalized[0] + " " + normalized[1]);
return(normalized);
}
//
// PRIVATE METHODS
//
private BayesNet createWetGrassNetwork()
{
BayesNetNode cloudy = new BayesNetNode("Cloudy");
BayesNetNode sprinkler = new BayesNetNode("Sprinkler");
BayesNetNode rain = new BayesNetNode("Rain");
BayesNetNode wetGrass = new BayesNetNode("WetGrass");
sprinkler.influencedBy(cloudy);
rain.influencedBy(cloudy);
wetGrass.influencedBy(rain, sprinkler);
cloudy.setProbability(true, 0.5);
sprinkler.setProbability(true, 0.10);
sprinkler.setProbability(false, 0.50);
rain.setProbability(true, 0.8);
rain.setProbability(false, 0.2);
wetGrass.setProbability(true, true, 0.99);
wetGrass.setProbability(true, false, 0.90);
wetGrass.setProbability(false, true, 0.90);
wetGrass.setProbability(false, false, 0.00);
BayesNet net = new BayesNet(cloudy);
return net;
}
public void setUp() {
net = createBurglaryNetwork();
}
