Algorithms refactor (#2136)

algorithms/src/main/java/com/baeldung/algorithms/automata/FiniteStateMachine.java

@@ -1,4 +1,4 @@
-package com.baeldung.automata;
+package com.baeldung.algorithms.automata;
 
 /**
  * Finite state machine.

algorithms/src/main/java/com/baeldung/algorithms/automata/RtFiniteStateMachine.java

@@ -1,4 +1,4 @@
-package com.baeldung.automata;
+package com.baeldung.algorithms.automata;
 
 /**
  * Default implementation of a finite state machine.

algorithms/src/main/java/com/baeldung/algorithms/automata/RtState.java

@@ -1,4 +1,4 @@
-package com.baeldung.automata;
+package com.baeldung.algorithms.automata;
 
 import java.util.ArrayList;
 import java.util.List;

algorithms/src/main/java/com/baeldung/algorithms/automata/RtTransition.java

@@ -1,4 +1,4 @@
-package com.baeldung.automata;
+package com.baeldung.algorithms.automata;
 
 
 /**

algorithms/src/main/java/com/baeldung/algorithms/automata/State.java

@@ -1,4 +1,4 @@
-package com.baeldung.automata;
+package com.baeldung.algorithms.automata;
 
 /**
  * State. Part of a finite state machine.

algorithms/src/main/java/com/baeldung/algorithms/automata/Transition.java

@@ -1,4 +1,4 @@
-package com.baeldung.automata;
+package com.baeldung.algorithms.automata;
 
 /**
  * Transition in a finite State machine.

algorithms/src/main/java/com/baeldung/algorithms/mcts/montecarlo/MonteCarloTreeSearch.java

@@ -8,9 +8,9 @@ import com.baeldung.algorithms.mcts.tree.Tree;
 
 public class MonteCarloTreeSearch {
 
-    static final int WIN_SCORE = 10;
-    int level;
-    int oponent;
+    private static final int WIN_SCORE = 10;
+    private int level;
+    private int oponent;
 
     public MonteCarloTreeSearch() {
         this.level = 3;

algorithms/src/main/java/com/baeldung/algorithms/mcts/montecarlo/State.java

@@ -7,10 +7,10 @@ import com.baeldung.algorithms.mcts.tictactoe.Board;
 import com.baeldung.algorithms.mcts.tictactoe.Position;
 
 public class State {
-    Board board;
-    int playerNo;
-    int visitCount;
-    double winScore;
+    private Board board;
+    private int playerNo;
+    private int visitCount;
+    private double winScore;
 
     public State() {
         board = new Board();
@@ -27,23 +27,23 @@ public class State {
         this.board = new Board(board);
     }
 
-    public Board getBoard() {
+    Board getBoard() {
         return board;
     }
 
-    public void setBoard(Board board) {
+    void setBoard(Board board) {
         this.board = board;
     }
 
-    public int getPlayerNo() {
+    int getPlayerNo() {
         return playerNo;
     }
 
-    public void setPlayerNo(int playerNo) {
+    void setPlayerNo(int playerNo) {
         this.playerNo = playerNo;
     }
 
-    public int getOpponent() {
+    int getOpponent() {
         return 3 - playerNo;
     }
 
@@ -55,11 +55,11 @@ public class State {
         this.visitCount = visitCount;
     }
 
-    public double getWinScore() {
+    double getWinScore() {
         return winScore;
     }
 
-    public void setWinScore(double winScore) {
+    void setWinScore(double winScore) {
         this.winScore = winScore;
     }
 
@@ -75,23 +75,23 @@ public class State {
         return possibleStates;
     }
 
-    public void incrementVisit() {
+    void incrementVisit() {
         this.visitCount++;
     }
 
-    public void addScore(double score) {
+    void addScore(double score) {
         if (this.winScore != Integer.MIN_VALUE)
             this.winScore += score;
     }
 
-    public void randomPlay() {
+    void randomPlay() {
         List<Position> availablePositions = this.board.getEmptyPositions();
         int totalPossibilities = availablePositions.size();
         int selectRandom = (int) (Math.random() * ((totalPossibilities - 1) + 1));
         this.board.performMove(this.playerNo, availablePositions.get(selectRandom));
     }
 
-    public void togglePlayer() {
+    void togglePlayer() {
         this.playerNo = 3 - this.playerNo;
     }
 }

algorithms/src/main/java/com/baeldung/algorithms/mcts/montecarlo/UCT.java

@@ -7,20 +7,18 @@ import java.util.List;
 import com.baeldung.algorithms.mcts.tree.Node;
 
 public class UCT {
-    final static double C = 1.41;
 
     public static double uctValue(int totalVisit, double nodeWinScore, int nodeVisit) {
-        if (nodeVisit == 0)
+        if (nodeVisit == 0) {
             return Integer.MAX_VALUE;
-        return ((double) nodeWinScore / (double) nodeVisit) + 1.41 * Math.sqrt(Math.log(totalVisit) / (double) nodeVisit);
+        }
+        return (nodeWinScore / (double) nodeVisit) + 1.41 * Math.sqrt(Math.log(totalVisit) / (double) nodeVisit);
     }
 
-    public static Node findBestNodeWithUCT(Node node) {
+    static Node findBestNodeWithUCT(Node node) {
         int parentVisit = node.getState().getVisitCount();
-        List<Node> childNodes = node.getChildArray();
-        return Collections.max(childNodes, Comparator.comparing(c -> {
-            double score = uctValue(parentVisit, c.getState().getWinScore(), c.getState().getVisitCount());
-            return score;
-        }));
+        return Collections.max(
+          node.getChildArray(),
+          Comparator.comparing(c -> uctValue(parentVisit, c.getState().getWinScore(), c.getState().getVisitCount())));
     }
 }

algorithms/src/test/java/algorithms/RtFiniteStateMachineLongRunningUnitTest.java

@@ -1,6 +1,6 @@
 package algorithms;
 
-import com.baeldung.automata.*;
+import com.baeldung.algorithms.automata.*;
 import org.junit.Test;
 
 import static org.junit.Assert.assertTrue;

algorithms/src/test/java/algorithms/mcts/MCTSTest.java

@@ -1,4 +1,4 @@
-package algorithms;
+package algorithms.mcts;
 
 import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertTrue;
@@ -16,8 +16,8 @@ import com.baeldung.algorithms.mcts.tictactoe.Position;
 import com.baeldung.algorithms.mcts.tree.Tree;
 
 public class MCTSTest {
-    Tree gameTree;
-    MonteCarloTreeSearch mcts;
+    private Tree gameTree;
+    private MonteCarloTreeSearch mcts;
 
     @Before
     public void initGameTree() {