Code polished.

Author: RuedigerLunde

aima-core/src/main/java/aima/core/search/csp/BacktrackingStrategy.java

@@ -1,5 +1,7 @@
 package aima.core.search.csp;
 
+import aima.core.util.CancelableThread;
+
 /**
  * Artificial Intelligence A Modern Approach (3rd Ed.): Figure 6.5, Page 215.<br>
  * <br>
@@ -51,7 +53,7 @@ public Assignment solve(CSP csp) {
 	private Assignment recursiveBackTrackingSearch(CSP csp,
 			Assignment assignment) {
 		Assignment result = null;
-		if (assignment.isComplete(csp.getVariables())) {
+		if (assignment.isComplete(csp.getVariables()) || CancelableThread.currIsCanceled()) {
 			result = assignment;
 		} else {
 			Variable var = selectUnassignedVariable(assignment, csp);

aima-gui/src/main/java/aima/gui/fx/applications/search/CspNQueensApp.java

@@ -9,6 +9,7 @@
 import aima.core.search.csp.SolutionStrategy;
 import aima.core.search.csp.Variable;
 import aima.core.search.csp.examples.NQueensCSP;
+import aima.core.search.framework.Metrics;
 import aima.core.util.datastructure.XYLocation;
 import aima.gui.fx.framework.IntegrableApplication;
 import aima.gui.fx.framework.Parameter;
@@ -125,7 +126,7 @@ public void simulate() {
 			NQueensBoard board = getBoard(solution);
 			stateViewCtrl.update(board);
 		}
-		simPaneCtrl.setStatus(progressAnalyzer.getResults());
+		simPaneCtrl.setStatus(progressAnalyzer.getResults().toString());
 	}
 
 	private NQueensBoard getBoard(Assignment assignment) {
@@ -166,13 +167,13 @@ public void reset() {
 			assignmentCount = 0;
 			domainCount = 0;
 		}
-		
-		public String getResults() {
-			StringBuffer result = new StringBuffer();
-			result.append("assignment changes: " + assignmentCount);
+
+		public Metrics getResults() {
+			Metrics result = new Metrics();
+			result.set("assignmentChanges", assignmentCount);
 			if (domainCount != 0)
-				result.append(", domain changes: " + domainCount);
-			return result.toString();
+				result.set("domainChanges", domainCount);
+			return result;
 		}
 	}
 

aima-gui/src/main/java/aima/gui/fx/applications/search/CspNQueensDemo.java

@@ -8,6 +8,7 @@
 import aima.core.search.csp.MinConflictsStrategy;
 import aima.core.search.csp.SolutionStrategy;
 import aima.core.search.csp.examples.NQueensCSP;
+import aima.core.search.framework.Metrics;
 
 public class CspNQueensDemo {
 	public static void main(String[] args) {
@@ -62,12 +63,12 @@ public void reset() {
 			domainCount = 0;
 		}
 
-		public String getResults() {
-			StringBuffer result = new StringBuffer();
-			result.append("assignment changes: " + assignmentCount);
+		public Metrics getResults() {
+			Metrics result = new Metrics();
+			result.set("assignmentChanges", assignmentCount);
 			if (domainCount != 0)
-				result.append(", domain changes: " + domainCount);
-			return result.toString();
+				result.set("domainChanges", domainCount);
+			return result;
 		}
 	}
 }

aima-gui/src/main/java/aima/gui/fx/applications/search/games/EightPuzzleApp.java

@@ -16,6 +16,7 @@
 import aima.core.search.framework.qsearch.GraphSearch;
 import aima.core.search.informed.AStarSearch;
 import aima.core.search.informed.GreedyBestFirstSearch;
+import aima.core.search.local.Scheduler;
 import aima.core.search.local.SimulatedAnnealingSearch;
 import aima.core.search.uninformed.BreadthFirstSearch;
 import aima.core.search.uninformed.DepthLimitedSearch;
@@ -64,16 +65,16 @@ public static void addSearchAlgorithm(String name, SearchForActions algo) {
 				new BreadthFirstSearch(new BidirectionalSearch()));
 		addSearchAlgorithm("Depth Limited Search (9)", new DepthLimitedSearch(9));
 		addSearchAlgorithm("Iterative Deepening Search", new IterativeDeepeningSearch());
-		addSearchAlgorithm("Greedy Best First Search (MisplacedTileHeursitic)",
+		addSearchAlgorithm("Greedy Best First Search (MisplacedTileHeuristic)",
 				new GreedyBestFirstSearch(new GraphSearch(), new MisplacedTilleHeuristicFunction()));
-		addSearchAlgorithm("Greedy Best First Search (ManhattanHeursitic)",
+		addSearchAlgorithm("Greedy Best First Search (ManhattanHeuristic)",
 				new GreedyBestFirstSearch(new GraphSearch(), new ManhattanHeuristicFunction()));
-		addSearchAlgorithm("AStar Search (MisplacedTileHeursitic)",
+		addSearchAlgorithm("AStar Search (MisplacedTileHeuristic)",
 				new AStarSearch(new GraphSearch(), new MisplacedTilleHeuristicFunction()));
-		addSearchAlgorithm("AStar Search (ManhattanHeursitic)",
+		addSearchAlgorithm("AStar Search (ManhattanHeuristic)",
 				new AStarSearch(new GraphSearch(), new ManhattanHeuristicFunction()));
-		addSearchAlgorithm("Simulated Annealing Search",
-				new SimulatedAnnealingSearch(new ManhattanHeuristicFunction()));
+		addSearchAlgorithm("Simulated Annealing Search (ManhattanHeuristic)",
+				new SimulatedAnnealingSearch(new ManhattanHeuristicFunction(), new Scheduler(20, 0.05, 200)));
 	}
 
 
@@ -178,7 +179,9 @@ else if (action == EightPuzzleBoard.LEFT)
 				board.moveGapLeft();
 			else if (action == EightPuzzleBoard.RIGHT)
 				board.moveGapRight();
-			updateStateView(null);
+			Metrics m = new Metrics();
+			m.set("manhattanHeuristic", new ManhattanHeuristicFunction().h(board));
+			updateStateView(m);
 			if (CancelableThread.currIsCanceled())
 				break;
 			simPaneCtrl.waitAfterStep();