Add tests, remove main in MonteCarloTreeSearch (#5673)

This commit is contained in:
Hardik Pawar
2024-10-11 01:50:39 +05:30
committed by GitHub
parent b1724fa737
commit e8b32513c8
3 changed files with 127 additions and 6 deletions

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@ -1010,6 +1010,7 @@
* [JumpSearchTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/searches/JumpSearchTest.java)
* [KMPSearchTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/searches/KMPSearchTest.java)
* [LinearSearchTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/searches/LinearSearchTest.java)
* [MonteCarloTreeSearchTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/searches/MonteCarloTreeSearchTest.java)
* [OrderAgnosticBinarySearchTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/searches/OrderAgnosticBinarySearchTest.java)
* [PerfectBinarySearchTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/searches/PerfectBinarySearchTest.java)
* [QuickSelectTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/searches/QuickSelectTest.java)

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@ -39,12 +39,6 @@ public class MonteCarloTreeSearch {
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.

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@ -0,0 +1,126 @@
package com.thealgorithms.searches;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertFalse;
import static org.junit.jupiter.api.Assertions.assertNotNull;
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");
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) {
assertFalse(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;
child.score = i * 2;
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");
}
}