Add tests, remove main in MonteCarloTreeSearch

Author: Hardvan

src/main/java/com/thealgorithms/searches/MonteCarloTreeSearch.java

@@ -39,12 +39,6 @@ public Node(Node parent, boolean isPlayersTurn) {
     static final int WIN_SCORE = 10;
     static final int TIME_LIMIT = 500; // Time the algorithm will be running for (in milliseconds).
 
-    public static void main(String[] args) {
-        MonteCarloTreeSearch mcts = new MonteCarloTreeSearch();
-
-        mcts.monteCarloTreeSearch(mcts.new Node(null, true));
-    }
-
     /**
      * Explores a game tree using Monte Carlo Tree Search (MCTS) and returns the
      * most promising node.

src/test/java/com/thealgorithms/searches/MonteCarloTreeSearchTest.java

@@ -0,0 +1,127 @@
+package com.thealgorithms.searches;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertNotNull;
+import static org.junit.jupiter.api.Assertions.assertNull;
+import static org.junit.jupiter.api.Assertions.assertTrue;
+
+import org.junit.jupiter.api.Test;
+
+class MonteCarloTreeSearchTest {
+
+    /**
+     * Test the creation of a node and its initial state.
+     */
+    @Test
+    void testNodeCreation() {
+        MonteCarloTreeSearch.Node node = new MonteCarloTreeSearch().new Node(null, true);
+        assertNotNull(node, "Node should be created");
+        assertNull(node.parent, "Parent should be null for root node");
+        assertTrue(node.childNodes.isEmpty(), "Child nodes should be empty upon creation");
+        assertTrue(node.isPlayersTurn, "Initial turn should be player's turn");
+        assertEquals(0, node.score, "Initial score should be zero");
+        assertEquals(0, node.visitCount, "Initial visit count should be zero");
+    }
+
+    /**
+     * Test adding child nodes to a parent node.
+     */
+    @Test
+    void testAddChildNodes() {
+        MonteCarloTreeSearch mcts = new MonteCarloTreeSearch();
+        MonteCarloTreeSearch.Node parentNode = mcts.new Node(null, true);
+
+        mcts.addChildNodes(parentNode, 5);
+
+        assertEquals(5, parentNode.childNodes.size(), "Parent should have 5 child nodes");
+        for (MonteCarloTreeSearch.Node child : parentNode.childNodes) {
+            assertEquals(false, child.isPlayersTurn, "Child node should not be player's turn");
+            assertEquals(0, child.visitCount, "Child node visit count should be zero");
+        }
+    }
+
+    /**
+     * Test the UCT selection of a promising node.
+     */
+    @Test
+    void testGetPromisingNode() {
+        MonteCarloTreeSearch mcts = new MonteCarloTreeSearch();
+        MonteCarloTreeSearch.Node parentNode = mcts.new Node(null, true);
+
+        // Create child nodes with different visit counts and scores
+        for (int i = 0; i < 3; i++) {
+            MonteCarloTreeSearch.Node child = mcts.new Node(parentNode, false);
+            child.visitCount = i + 1; // Visits 1, 2, 3
+            child.score = i * 2; // Scores 0, 2, 4
+            parentNode.childNodes.add(child);
+        }
+
+        // Get promising node
+        MonteCarloTreeSearch.Node promisingNode = mcts.getPromisingNode(parentNode);
+
+        // The child with the highest UCT value should be chosen.
+        assertNotNull(promisingNode, "Promising node should not be null");
+        assertEquals(0, parentNode.childNodes.indexOf(promisingNode), "The first child should be the most promising");
+    }
+
+    /**
+     * Test simulation of random play and backpropagation.
+     */
+    @Test
+    void testSimulateRandomPlay() {
+        MonteCarloTreeSearch mcts = new MonteCarloTreeSearch();
+        MonteCarloTreeSearch.Node node = mcts.new Node(null, true);
+        node.visitCount = 10; // Simulating existing visits
+
+        // Simulate random play
+        mcts.simulateRandomPlay(node);
+
+        // Check visit count after simulation
+        assertEquals(11, node.visitCount, "Visit count should increase after simulation");
+
+        // Check if score is updated correctly
+        assertTrue(node.score >= 0 && node.score <= MonteCarloTreeSearch.WIN_SCORE, "Score should be between 0 and WIN_SCORE");
+    }
+
+    /**
+     * Test retrieving the winning node based on scores.
+     */
+    @Test
+    void testGetWinnerNode() {
+        MonteCarloTreeSearch mcts = new MonteCarloTreeSearch();
+        MonteCarloTreeSearch.Node parentNode = mcts.new Node(null, true);
+
+        // Create child nodes with varying scores
+        MonteCarloTreeSearch.Node winningNode = mcts.new Node(parentNode, false);
+        winningNode.score = 10; // Highest score
+        parentNode.childNodes.add(winningNode);
+
+        MonteCarloTreeSearch.Node losingNode = mcts.new Node(parentNode, false);
+        losingNode.score = 5;
+        parentNode.childNodes.add(losingNode);
+
+        MonteCarloTreeSearch.Node anotherLosingNode = mcts.new Node(parentNode, false);
+        anotherLosingNode.score = 3;
+        parentNode.childNodes.add(anotherLosingNode);
+
+        // Get the winning node
+        MonteCarloTreeSearch.Node winnerNode = mcts.getWinnerNode(parentNode);
+
+        assertEquals(winningNode, winnerNode, "Winning node should have the highest score");
+    }
+
+    /**
+     * Test the full Monte Carlo Tree Search process.
+     */
+    @Test
+    void testMonteCarloTreeSearch() {
+        MonteCarloTreeSearch mcts = new MonteCarloTreeSearch();
+        MonteCarloTreeSearch.Node rootNode = mcts.new Node(null, true);
+
+        // Execute MCTS and check the resulting node
+        MonteCarloTreeSearch.Node optimalNode = mcts.monteCarloTreeSearch(rootNode);
+
+        assertNotNull(optimalNode, "MCTS should return a non-null optimal node");
+        assertTrue(rootNode.childNodes.contains(optimalNode), "Optimal node should be a child of the root");
+    }
+}