Added Daniel's Bayes Net code. Converted example code to unit tests. Minor code clean-up.

2012-03-11 10:33:45 -04:00
parent a021dc2fc0
commit 571d0a1922
27 changed files with 2310 additions and 0 deletions
--- a/test/dkohl/bayes/example/builders/AlarmNetBuilderTable.java
+++ b/test/dkohl/bayes/example/builders/AlarmNetBuilderTable.java
@@ -0,0 +1,176 @@
+package dkohl.bayes.example.builders;
+
+import java.util.LinkedList;
+
+import dkohl.bayes.bayesnet.BayesNet;
+import dkohl.bayes.probability.Assignment;
+import dkohl.bayes.probability.Probability;
+import dkohl.bayes.probability.Variable;
+import dkohl.bayes.probability.distribution.ProbabilityTable;
+
+/**
+ * The alarm example for baysian nets.
+ * 
+ * Stuart Russel, Peter Norvig: Artificial Intelligence: A Modern Approach, 3ed
+ * Edition, Prentice Hall, 2010
+ * 
+ * @author Daniel Kohlsdorf
+ */
+public class AlarmNetBuilderTable {
+
+	// Variable names
+	public static final String BURGLARY = "Burglary";
+	public static final String EARTHQUAKE = "Earthquake";
+	public static final String ALARM = "Alarm";
+	public static final String JOHN = "John";
+	public static final String MARRY = "Marry";
+
+	// Possible outcomes
+	public static final String TRUE = "true";
+	public static final String FALSE = "false";
+
+	// A variables domain
+	public static final String DOMAIN[] = { TRUE, FALSE };
+
+	// A set of variables
+	public static final String VARIABLES[] = { BURGLARY, EARTHQUAKE, ALARM,
+			JOHN, MARRY };
+
+	/**
+	 * Builds the query from the book: P(B| j, m)
+	 */
+	public static LinkedList<Assignment> completeQueryBulgary() {
+		LinkedList<Assignment> assignment = new LinkedList<Assignment>();
+		assignment.add(new Assignment(new Variable(JOHN, DOMAIN), TRUE));
+		assignment.add(new Assignment(new Variable(MARRY, DOMAIN), TRUE));
+		return new LinkedList<Assignment>(assignment);
+	}
+
+	/**
+	 * Build burglary prior
+	 * 
+	 * @param alarmNet
+	 */
+	private static void burglary(BayesNet alarmNet) {
+		Probability p_bulglary = new Probability(0.001);
+		String names[] = { BURGLARY };
+		ProbabilityTable burglary = new ProbabilityTable(names);
+		burglary.setProbabilityForAssignment("true;", p_bulglary);
+		burglary.setProbabilityForAssignment("false;", p_bulglary.rest());
+		alarmNet.setDistribution(new Variable(BURGLARY, DOMAIN), burglary);
+	}
+
+	/**
+	 * Build earthquake prior
+	 * 
+	 * @param alarmNet
+	 */
+	private static void earthquake(BayesNet alarmNet) {
+		Probability p_earthquake = new Probability(0.002);
+		String names[] = { EARTHQUAKE };
+		ProbabilityTable earthquake = new ProbabilityTable(names);
+		earthquake.setProbabilityForAssignment("true;", p_earthquake);
+		earthquake.setProbabilityForAssignment("false;", p_earthquake.rest());
+
+		alarmNet.setDistribution(new Variable(EARTHQUAKE, DOMAIN), earthquake);
+	}
+
+	/**
+	 * Jhon calls!
+	 * 
+	 * @param alarmNet
+	 */
+	private static void jhon(BayesNet alarmNet) {
+		// P(ALARM) == true
+		Probability t = new Probability(.90);
+
+		// P(ALARM) == false
+		Probability f = new Probability(.05);
+		String names[] = { ALARM, JOHN };
+		ProbabilityTable jhon = new ProbabilityTable(names);
+		jhon.setProbabilityForAssignment("true;true;", t);
+		jhon.setProbabilityForAssignment("false;true;", f);
+		jhon.setProbabilityForAssignment("true;false", t.rest());
+		jhon.setProbabilityForAssignment("false;false;", f.rest());
+
+		alarmNet.setDistribution(new Variable(JOHN, DOMAIN), jhon);
+	}
+
+	/**
+	 * Marry calls!
+	 * 
+	 * @param alarmNet
+	 */
+	private static void mary(BayesNet alarmNet) {
+		// P(ALARM) == true
+		Probability t = new Probability(.70);
+
+		// P(ALARM) == false
+		Probability f = new Probability(.01);
+		String names[] = { ALARM, MARRY };
+		ProbabilityTable marry = new ProbabilityTable(names);
+		marry.setProbabilityForAssignment("true;true;", t);
+		marry.setProbabilityForAssignment("false;true;", f);
+		marry.setProbabilityForAssignment("true;false", t.rest());
+		marry.setProbabilityForAssignment("false;false;", f.rest());
+		alarmNet.setDistribution(new Variable(MARRY, DOMAIN), marry);
+	}
+
+	/**
+	 * The alarm goes off!
+	 * 
+	 * @param alarmNet
+	 */
+	private static void alarm(BayesNet alarmNet) {
+		// P(ALARM | BURGLARY = true, EARTHQUAKE = true)
+		Probability tt = new Probability(.95);
+
+		// P(ALARM | BURGLARY = true, EARTHQUAKE = false)
+		Probability tf = new Probability(.94);
+
+		// P(ALARM | BURGLARY = false, EARTHQUAKE = true)
+		Probability ft = new Probability(.29);
+
+		// P(ALARM | BURGLARY = false, EARTHQUAKE = false)
+		Probability ff = new Probability(.001);
+		String names[] = { BURGLARY, EARTHQUAKE, ALARM };
+		ProbabilityTable alarm = new ProbabilityTable(names);
+		alarm.setProbabilityForAssignment(TRUE + ";" + TRUE + ";" + TRUE + ";",
+				tt);
+		alarm.setProbabilityForAssignment(
+				TRUE + ";" + FALSE + ";" + TRUE + ";", tf);
+		alarm.setProbabilityForAssignment(
+				FALSE + ";" + TRUE + ";" + TRUE + ";", ft);
+		alarm.setProbabilityForAssignment(FALSE + ";" + FALSE + ";" + TRUE
+				+ ";", ff);
+
+		alarm.setProbabilityForAssignment(
+				TRUE + ";" + TRUE + ";" + FALSE + ";", tt.rest());
+		alarm.setProbabilityForAssignment(TRUE + ";" + FALSE + ";" + FALSE
+				+ ";", tf.rest());
+		alarm.setProbabilityForAssignment(FALSE + ";" + TRUE + ";" + FALSE
+				+ ";", ft.rest());
+		alarm.setProbabilityForAssignment(FALSE + ";" + FALSE + ";" + FALSE
+				+ ";", ff.rest());
+		alarmNet.setDistribution(new Variable(ALARM, DOMAIN), alarm);
+	}
+
+	public static BayesNet alarm() {
+		BayesNet alarmNet = new BayesNet(VARIABLES);
+
+		// set probability tables and priors
+		burglary(alarmNet);
+		earthquake(alarmNet);
+		alarm(alarmNet);
+		jhon(alarmNet);
+		mary(alarmNet);
+
+		// construct the graph
+		alarmNet.connect(ALARM, BURGLARY);
+		alarmNet.connect(ALARM, EARTHQUAKE);
+		alarmNet.connect(JOHN, ALARM);
+		alarmNet.connect(MARRY, ALARM);
+
+		return alarmNet;
+	}
+}