Documentation improved.

Author: RuedigerLunde

aima-core/src/main/java/aima/core/search/informed/AStarSearch.java

@@ -22,11 +22,11 @@
 public class AStarSearch extends BestFirstSearch {
 
 	/**
-	 * Constructs an A* search from the specified search problem and heuristic
-	 * function
+	 * Constructs an A* search from a specified search space exploration
+	 * strategy and a heuristic function.
 	 * 
 	 * @param impl
-	 *            a search space exploration strategy.
+	 *            a search space exploration strategy (e.g. TreeSearch, GraphSearch).
 	 * @param hf
 	 *            a heuristic function <em>h(n)</em>, which estimates the cost
 	 *            of the cheapest path from the state at node <em>n</em> to a

aima-core/src/main/java/aima/core/search/informed/GreedyBestFirstSearch.java

@@ -16,11 +16,12 @@
 public class GreedyBestFirstSearch extends BestFirstSearch {
 
 	/**
-	 * Constructs a greedy best-first search from the specified search problem
-	 * and heuristic function.
+	 * Constructs a greedy best-first search from a specified search space
+	 * exploration strategy and a heuristic function.
 	 * 
 	 * @param impl
-	 *            a search space exploration strategy.
+	 *            a search space exploration strategy (e.g. TreeSearch,
+	 *            GraphSearch).
 	 * @param hf
 	 *            a heuristic function <em>h(n)</em>, which estimates the
 	 *            cheapest path from the state at node <em>n</em> to a goal

aima-core/src/main/java/aima/core/search/informed/HeuristicEvaluationFunction.java

@@ -5,17 +5,18 @@
 import aima.core.search.framework.evalfunc.HeuristicFunction;
 
 /**
- * Informed search algorithms use special evaluation functions which are based
- * on heuristics to estimate remaining costs to reach a goal state from a given
- * node. They only differ in the way how they combine the estimated remaining
- * costs with the costs of the already known path to the node.
+ * Super class for all evaluation functions which make use of heuristics.
+ * Informed search algorithms use heuristics to estimate remaining costs to
+ * reach a goal state from a given node. Their evaluation functions only differ
+ * in the way how they combine the estimated remaining costs with the costs of
+ * the already known path to the node.
  * 
  * @author Ruediger Lunde
  *
  */
 public abstract class HeuristicEvaluationFunction implements EvaluationFunction {
 	protected HeuristicFunction hf = SearchUtils.getZeroHeuristic();
-	
+
 	public HeuristicFunction getHeuristicFunction() {
 		return hf;
 	}