mirror of
https://github.com/2OOP/pism.git
synced 2026-02-04 10:54:51 +00:00
merge commit
This commit is contained in:
@@ -1,12 +1,9 @@
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package org.toop;
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package org.toop;
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import org.toop.app.App;
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import org.toop.app.App;
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import org.toop.framework.machinelearning.NeuralNetwork;
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public final class Main {
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public final class Main {
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static void main(String[] args) {
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static void main(String[] args) {
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App.run(args);
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App.run(args);
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NeuralNetwork nn = new NeuralNetwork();
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nn.init();
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}
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}
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}
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}
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@@ -15,6 +15,7 @@ import org.toop.framework.audio.*;
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import org.toop.framework.audio.events.AudioEvents;
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import org.toop.framework.audio.events.AudioEvents;
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import org.toop.framework.eventbus.EventFlow;
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import org.toop.framework.eventbus.EventFlow;
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import org.toop.framework.eventbus.GlobalEventBus;
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import org.toop.framework.eventbus.GlobalEventBus;
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import org.toop.game.machinelearning.NeuralNetwork;
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import org.toop.framework.networking.NetworkingClientEventListener;
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import org.toop.framework.networking.NetworkingClientEventListener;
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import org.toop.framework.networking.NetworkingClientManager;
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import org.toop.framework.networking.NetworkingClientManager;
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import org.toop.framework.resource.ResourceLoader;
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import org.toop.framework.resource.ResourceLoader;
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@@ -138,8 +139,14 @@ public final class App extends Application {
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stage.show();
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stage.show();
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//startML();
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}
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}
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private void startML() {
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NeuralNetwork nn = new NeuralNetwork();
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nn.init();
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}
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private void setKeybinds(StackPane root) {
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private void setKeybinds(StackPane root) {
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root.addEventHandler(KeyEvent.KEY_PRESSED,event -> {
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root.addEventHandler(KeyEvent.KEY_PRESSED,event -> {
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if (event.getCode() == KeyCode.ESCAPE) {
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if (event.getCode() == KeyCode.ESCAPE) {
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@@ -1,334 +0,0 @@
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package org.toop.app.game;
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import javafx.animation.SequentialTransition;
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import org.toop.app.App;
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import org.toop.app.GameInformation;
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import org.toop.app.canvas.ReversiCanvas;
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import org.toop.app.widget.WidgetContainer;
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import org.toop.app.widget.view.GameView;
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import org.toop.framework.eventbus.EventFlow;
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import org.toop.framework.networking.events.NetworkEvents;
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import org.toop.game.enumerators.GameState;
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import org.toop.game.records.Move;
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import org.toop.game.reversi.Reversi;
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import org.toop.game.reversi.ReversiAI;
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import javafx.geometry.Pos;
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import javafx.scene.paint.Color;
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import org.toop.game.reversi.ReversiAIML;
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import java.awt.*;
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import java.util.concurrent.BlockingQueue;
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import java.util.concurrent.LinkedBlockingQueue;
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import java.util.concurrent.atomic.AtomicBoolean;
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import java.util.function.Consumer;
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public final class ReversiGame {
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private final GameInformation information;
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private final int myTurn;
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private final Runnable onGameOver;
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private final BlockingQueue<Move> moveQueue;
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private final Reversi game;
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private final ReversiAIML ai;
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private final GameView primary;
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private final ReversiCanvas canvas;
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private final AtomicBoolean isRunning;
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private final AtomicBoolean isPaused;
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public ReversiGame(GameInformation information, int myTurn, Runnable onForfeit, Runnable onExit, Consumer<String> onMessage, Runnable onGameOver) {
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this.information = information;
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this.myTurn = myTurn;
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this.onGameOver = onGameOver;
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moveQueue = new LinkedBlockingQueue<>();
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game = new Reversi();
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ai = new ReversiAIML();
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isRunning = new AtomicBoolean(true);
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isPaused = new AtomicBoolean(false);
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if (onForfeit == null || onExit == null) {
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primary = new GameView(null, () -> {
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isRunning.set(false);
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WidgetContainer.getCurrentView().transitionPrevious();
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}, null, "Reversi");
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} else {
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primary = new GameView(onForfeit, () -> {
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isRunning.set(false);
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onExit.run();
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}, onMessage, "Reversi");
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}
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canvas = new ReversiCanvas(Color.BLACK,
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(App.getHeight() / 4) * 3, (App.getHeight() / 4) * 3,
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(cell) -> {
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if (onForfeit == null || onExit == null) {
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if (information.players[game.getCurrentTurn()].isHuman) {
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final char value = game.getCurrentTurn() == 0? 'B' : 'W';
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try {
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moveQueue.put(new Move(cell, value));
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} catch (InterruptedException _) {}
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}
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} else {
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if (information.players[0].isHuman) {
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final char value = myTurn == 0? 'B' : 'W';
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try {
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moveQueue.put(new Move(cell, value));
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} catch (InterruptedException _) {}
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}
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}
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},this::highlightCells);
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primary.add(Pos.CENTER, canvas.getCanvas());
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WidgetContainer.getCurrentView().transitionNext(primary);
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if (onForfeit == null || onExit == null) {
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new Thread(this::localGameThread).start();
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setGameLabels(information.players[0].isHuman);
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} else {
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new EventFlow()
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.listen(NetworkEvents.GameMoveResponse.class, this::onMoveResponse)
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.listen(NetworkEvents.YourTurnResponse.class, this::onYourTurnResponse);
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setGameLabels(myTurn == 0);
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}
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updateCanvas(false);
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}
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public ReversiGame(GameInformation information) {
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this(information, 0, null, null, null,null);
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}
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private void localGameThread() {
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while (isRunning.get()) {
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if (isPaused.get()) {
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try {
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Thread.sleep(200);
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} catch (InterruptedException _) {}
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continue;
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}
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final int currentTurn = game.getCurrentTurn();
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final String currentValue = currentTurn == 0? "BLACK" : "WHITE";
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final int nextTurn = (currentTurn + 1) % information.type.getPlayerCount();
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primary.nextPlayer(information.players[currentTurn].isHuman,
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information.players[currentTurn].name,
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currentValue,
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information.players[nextTurn].name);
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Move move = null;
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if (information.players[currentTurn].isHuman) {
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try {
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final Move wants = moveQueue.take();
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final Move[] legalMoves = game.getLegalMoves();
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for (final Move legalMove : legalMoves) {
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if (legalMove.position() == wants.position() &&
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legalMove.value() == wants.value()) {
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move = wants;
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break;
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}
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}
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} catch (InterruptedException _) {}
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} else {
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final long start = System.currentTimeMillis();
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move = ai.findBestMove(game, information.players[currentTurn].computerDifficulty);
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if (information.players[currentTurn].computerThinkTime > 0) {
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final long elapsedTime = System.currentTimeMillis() - start;
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final long sleepTime = information.players[currentTurn].computerThinkTime * 1000L - elapsedTime;
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try {
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Thread.sleep((long) (sleepTime * Math.random()));
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} catch (InterruptedException _) {}
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}
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}
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if (move == null) {
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continue;
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}
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canvas.setCurrentlyHighlightedMovesNull();
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final GameState state = game.play(move);
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updateCanvas(true);
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if (state != GameState.NORMAL) {
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if (state == GameState.TURN_SKIPPED){
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continue;
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}
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int winningPLayerNumber = getPlayerNumberWithHighestScore();
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if (state == GameState.WIN && winningPLayerNumber > -1) {
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primary.gameOver(true, information.players[winningPLayerNumber].name);
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} else if (state == GameState.DRAW || winningPLayerNumber == -1) {
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primary.gameOver(false, "");
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}
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isRunning.set(false);
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}
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}
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}
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private int getPlayerNumberWithHighestScore(){
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Reversi.Score score = game.getScore();
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if (score.player1Score() > score.player2Score()) return 0;
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if (score.player1Score() < score.player2Score()) return 1;
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return -1;
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}
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private void onMoveResponse(NetworkEvents.GameMoveResponse response) {
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if (!isRunning.get()) {
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return;
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}
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char playerChar;
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if (response.player().equalsIgnoreCase(information.players[0].name)) {
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playerChar = myTurn == 0? 'B' : 'W';
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} else {
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playerChar = myTurn == 0? 'W' : 'B';
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}
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final Move move = new Move(Integer.parseInt(response.move()), playerChar);
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final GameState state = game.play(move);
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if (state != GameState.NORMAL) {
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if (state == GameState.WIN) {
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if (response.player().equalsIgnoreCase(information.players[0].name)) {
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primary.gameOver(true, information.players[0].name);
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gameOver();
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} else {
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primary.gameOver(false, information.players[1].name);
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gameOver();
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}
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} else if (state == GameState.DRAW) {
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primary.gameOver(false, "");
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game.play(move);
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}
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}
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updateCanvas(false);
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setGameLabels(game.getCurrentTurn() == myTurn);
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}
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private void gameOver() {
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if (onGameOver == null){
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return;
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}
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isRunning.set(false);
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onGameOver.run();
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}
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private void onYourTurnResponse(NetworkEvents.YourTurnResponse response) {
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if (!isRunning.get()) {
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return;
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}
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moveQueue.clear();
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int position = -1;
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|
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if (information.players[0].isHuman) {
|
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try {
|
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position = moveQueue.take().position();
|
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} catch (InterruptedException _) {}
|
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} else {
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final Move move = ai.findBestMove(game, information.players[0].computerDifficulty);
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assert move != null;
|
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position = move.position();
|
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}
|
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|
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new EventFlow().addPostEvent(new NetworkEvents.SendMove(response.clientId(), (short) position))
|
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.postEvent();
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}
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|
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private void updateCanvas(boolean animate) {
|
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// Todo: this is very inefficient. still very fast but if the grid is bigger it might cause issues. improve.
|
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canvas.clearAll();
|
|
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|
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for (int i = 0; i < game.getBoard().length; i++) {
|
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if (game.getBoard()[i] == 'B') {
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canvas.drawDot(Color.BLACK, i);
|
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} else if (game.getBoard()[i] == 'W') {
|
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canvas.drawDot(Color.WHITE, i);
|
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}
|
|
||||||
}
|
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|
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final Move[] flipped = game.getMostRecentlyFlippedPieces();
|
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|
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final SequentialTransition animation = new SequentialTransition();
|
|
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isPaused.set(true);
|
|
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|
|
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final Color fromColor = game.getCurrentPlayer() == 'W'? Color.WHITE : Color.BLACK;
|
|
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final Color toColor = game.getCurrentPlayer() == 'W'? Color.BLACK : Color.WHITE;
|
|
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|
|
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if (animate && flipped != null) {
|
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for (final Move flip : flipped) {
|
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canvas.clear(flip.position());
|
|
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canvas.drawDot(fromColor, flip.position());
|
|
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animation.getChildren().addFirst(canvas.flipDot(fromColor, toColor, flip.position()));
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
animation.setOnFinished(_ -> {
|
|
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isPaused.set(false);
|
|
||||||
|
|
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if (information.players[game.getCurrentTurn()].isHuman) {
|
|
||||||
final Move[] legalMoves = game.getLegalMoves();
|
|
||||||
|
|
||||||
for (final Move legalMove : legalMoves) {
|
|
||||||
canvas.drawLegalPosition(legalMove.position(), game.getCurrentPlayer());
|
|
||||||
}
|
|
||||||
}
|
|
||||||
});
|
|
||||||
|
|
||||||
animation.play();
|
|
||||||
}
|
|
||||||
|
|
||||||
private void setGameLabels(boolean isMe) {
|
|
||||||
final int currentTurn = game.getCurrentTurn();
|
|
||||||
final String currentValue = currentTurn == 0? "BLACK" : "WHITE";
|
|
||||||
|
|
||||||
primary.nextPlayer(isMe,
|
|
||||||
information.players[isMe? 0 : 1].name,
|
|
||||||
currentValue,
|
|
||||||
information.players[isMe? 1 : 0].name);
|
|
||||||
}
|
|
||||||
|
|
||||||
private void highlightCells(int cellEntered) {
|
|
||||||
if (information.players[game.getCurrentTurn()].isHuman) {
|
|
||||||
Move[] legalMoves = game.getLegalMoves();
|
|
||||||
boolean isLegalMove = false;
|
|
||||||
for (Move move : legalMoves) {
|
|
||||||
if (move.position() == cellEntered){
|
|
||||||
isLegalMove = true;
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
if (cellEntered >= 0){
|
|
||||||
Move[] moves = null;
|
|
||||||
if (isLegalMove) {
|
|
||||||
moves = game.getFlipsForPotentialMove(
|
|
||||||
new Point(cellEntered%game.getColumnSize(),cellEntered/game.getRowSize()),
|
|
||||||
game.getCurrentPlayer(), game.getCurrentPlayer() == 'B'?'W':'B',game.makeBoardAGrid());
|
|
||||||
}
|
|
||||||
canvas.drawHighlightDots(moves);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@@ -152,12 +152,6 @@
|
|||||||
<version>1.0.0-M2.1</version>
|
<version>1.0.0-M2.1</version>
|
||||||
<scope>compile</scope>
|
<scope>compile</scope>
|
||||||
</dependency>
|
</dependency>
|
||||||
<dependency>
|
|
||||||
<groupId>org.toop</groupId>
|
|
||||||
<artifactId>game</artifactId>
|
|
||||||
<version>0.1</version>
|
|
||||||
<scope>compile</scope>
|
|
||||||
</dependency>
|
|
||||||
</dependencies>
|
</dependencies>
|
||||||
|
|
||||||
<build>
|
<build>
|
||||||
|
|||||||
@@ -1,18 +1,17 @@
|
|||||||
package org.toop.game.reversi;
|
package org.toop.game.games.reversi;
|
||||||
|
|
||||||
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
|
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
|
||||||
import org.deeplearning4j.util.ModelSerializer;
|
import org.deeplearning4j.util.ModelSerializer;
|
||||||
import org.nd4j.linalg.api.ndarray.INDArray;
|
import org.nd4j.linalg.api.ndarray.INDArray;
|
||||||
import org.nd4j.linalg.factory.Nd4j;
|
import org.nd4j.linalg.factory.Nd4j;
|
||||||
import org.toop.game.AI;
|
import org.toop.framework.gameFramework.model.player.AbstractAI;
|
||||||
import org.toop.game.records.Move;
|
|
||||||
|
|
||||||
import java.io.IOException;
|
import java.io.IOException;
|
||||||
import java.io.InputStream;
|
import java.io.InputStream;
|
||||||
|
|
||||||
import static java.lang.Math.random;
|
import static java.lang.Math.random;
|
||||||
|
|
||||||
public class ReversiAIML extends AI<Reversi>{
|
public class ReversiAIML extends AbstractAI<ReversiR> {
|
||||||
|
|
||||||
MultiLayerNetwork model;
|
MultiLayerNetwork model;
|
||||||
|
|
||||||
@@ -24,35 +23,35 @@ public class ReversiAIML extends AI<Reversi>{
|
|||||||
} catch (IOException e) {}
|
} catch (IOException e) {}
|
||||||
}
|
}
|
||||||
|
|
||||||
public Move findBestMove(Reversi reversi, int depth){
|
private int pickLegalMove(INDArray prediction, ReversiR reversi) {
|
||||||
int[] input = reversi.getBoardInt();
|
|
||||||
|
|
||||||
INDArray boardInput = Nd4j.create(new int[][] { input });
|
|
||||||
INDArray prediction = model.output(boardInput);
|
|
||||||
|
|
||||||
int move = pickLegalMove(prediction,reversi);
|
|
||||||
return new Move(move, reversi.getCurrentPlayer());
|
|
||||||
}
|
|
||||||
|
|
||||||
private int pickLegalMove(INDArray prediction, Reversi reversi) {
|
|
||||||
double[] logits = prediction.toDoubleVector();
|
double[] logits = prediction.toDoubleVector();
|
||||||
Move[] legalMoves = reversi.getLegalMoves();
|
int[] legalMoves = reversi.getLegalMoves();
|
||||||
|
|
||||||
if (legalMoves.length == 0) return -1;
|
if (legalMoves.length == 0) return -1;
|
||||||
|
|
||||||
int bestMove = legalMoves[0].position();
|
int bestMove = legalMoves[0];
|
||||||
double bestVal = logits[bestMove];
|
double bestVal = logits[bestMove];
|
||||||
|
|
||||||
if (random() < 0.01){
|
if (random() < 0.01){
|
||||||
return legalMoves[(int)(random()*legalMoves.length-.5)].position();
|
return legalMoves[(int)(random()*legalMoves.length-.5)];
|
||||||
}
|
}
|
||||||
for (Move move : legalMoves) {
|
for (int move : legalMoves) {
|
||||||
int pos = move.position();
|
if (logits[move] > bestVal) {
|
||||||
if (logits[pos] > bestVal) {
|
bestMove = move;
|
||||||
bestMove = pos;
|
bestVal = logits[move];
|
||||||
bestVal = logits[pos];
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
return bestMove;
|
return bestMove;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@Override
|
||||||
|
public int getMove(ReversiR game) {
|
||||||
|
int[] input = game.getBoard();
|
||||||
|
|
||||||
|
INDArray boardInput = Nd4j.create(new int[][] { input });
|
||||||
|
INDArray prediction = model.output(boardInput);
|
||||||
|
|
||||||
|
int move = pickLegalMove(prediction,game);
|
||||||
|
return move;
|
||||||
|
}
|
||||||
}
|
}
|
||||||
@@ -1,28 +1,33 @@
|
|||||||
package org.toop.game.reversi;
|
package org.toop.game.games.reversi;
|
||||||
|
|
||||||
import org.toop.game.AI;
|
import org.toop.framework.gameFramework.model.player.AbstractAI;
|
||||||
import org.toop.game.records.Move;
|
|
||||||
|
|
||||||
import java.util.Arrays;
|
import java.awt.*;
|
||||||
|
|
||||||
public class ReversiAISimple extends AI<Reversi> {
|
public class ReversiAISimple extends AbstractAI<ReversiR> {
|
||||||
|
|
||||||
|
|
||||||
|
private int getNumberOfOptions(ReversiR game, int move){
|
||||||
|
ReversiR copy = game.deepCopy();
|
||||||
|
copy.play(move);
|
||||||
|
return copy.getLegalMoves().length;
|
||||||
|
}
|
||||||
|
|
||||||
|
private int getScore(ReversiR game, int move){
|
||||||
|
return game.getFlipsForPotentialMove(new Point(move%game.getColumnSize(),move/game.getRowSize()),game.getCurrentTurn()).length;
|
||||||
|
}
|
||||||
|
|
||||||
@Override
|
@Override
|
||||||
public Move findBestMove(Reversi game, int depth) {
|
public int getMove(ReversiR game) {
|
||||||
//IO.println("****START FIND BEST MOVE****");
|
|
||||||
|
|
||||||
Move[] moves = game.getLegalMoves();
|
int[] moves = game.getLegalMoves();
|
||||||
|
|
||||||
|
int bestMove;
|
||||||
//game.printBoard();
|
int bestMoveScore = moves[0];
|
||||||
//IO.println("Legal moves: " + Arrays.toString(moves));
|
int bestMoveOptions = moves[0];
|
||||||
|
|
||||||
Move bestMove;
|
|
||||||
Move bestMoveScore = moves[0];
|
|
||||||
Move bestMoveOptions = moves[0];
|
|
||||||
int bestScore = -1;
|
int bestScore = -1;
|
||||||
int bestOptions = -1;
|
int bestOptions = -1;
|
||||||
for (Move move : moves){
|
for (int move : moves){
|
||||||
int numOpt = getNumberOfOptions(game, move);
|
int numOpt = getNumberOfOptions(game, move);
|
||||||
if (numOpt > bestOptions) {
|
if (numOpt > bestOptions) {
|
||||||
bestOptions = numOpt;
|
bestOptions = numOpt;
|
||||||
@@ -50,14 +55,4 @@ public class ReversiAISimple extends AI<Reversi> {
|
|||||||
}
|
}
|
||||||
return bestMove;
|
return bestMove;
|
||||||
}
|
}
|
||||||
|
|
||||||
private int getNumberOfOptions(Reversi game, Move move){
|
|
||||||
Reversi copy = new Reversi(game);
|
|
||||||
copy.play(move);
|
|
||||||
return copy.getLegalMoves().length;
|
|
||||||
}
|
|
||||||
|
|
||||||
private int getScore(Reversi game, Move move){
|
|
||||||
return game.getFlipsForPotentialMove(move).length;
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
@@ -254,7 +254,24 @@ public final class ReversiR extends AbstractGame<ReversiR> {
|
|||||||
});
|
});
|
||||||
return Arrays.stream(moves).mapToInt(Integer::intValue).toArray();
|
return Arrays.stream(moves).mapToInt(Integer::intValue).toArray();
|
||||||
}
|
}
|
||||||
|
|
||||||
public int[] getMostRecentlyFlippedPieces() {
|
public int[] getMostRecentlyFlippedPieces() {
|
||||||
return mostRecentlyFlippedPieces;
|
return mostRecentlyFlippedPieces;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
public Score getScore() {
|
||||||
|
int[] board = getBoard();
|
||||||
|
int p1 = 0;
|
||||||
|
int p2 = 0;
|
||||||
|
for (int i = 0; i < this.getColumnSize() * this.getRowSize(); i++) {
|
||||||
|
if (board[i] == 1) {
|
||||||
|
p1 += 1;
|
||||||
|
}
|
||||||
|
if (board[i] == 2) {
|
||||||
|
p2 += 1;
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
|
return new Score(p1, p2);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
@@ -1,4 +1,4 @@
|
|||||||
package org.toop.framework.machinelearning;
|
package org.toop.game.machinelearning;
|
||||||
|
|
||||||
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
|
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
|
||||||
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
|
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
|
||||||
@@ -13,13 +13,14 @@ import org.nd4j.linalg.dataset.DataSet;
|
|||||||
import org.nd4j.linalg.factory.Nd4j;
|
import org.nd4j.linalg.factory.Nd4j;
|
||||||
import org.nd4j.linalg.learning.config.Adam;
|
import org.nd4j.linalg.learning.config.Adam;
|
||||||
import org.nd4j.linalg.lossfunctions.LossFunctions;
|
import org.nd4j.linalg.lossfunctions.LossFunctions;
|
||||||
import org.toop.game.AI;
|
import org.toop.framework.gameFramework.GameState;
|
||||||
import org.toop.game.enumerators.GameState;
|
import org.toop.framework.gameFramework.model.game.PlayResult;
|
||||||
import org.toop.game.records.Move;
|
import org.toop.framework.gameFramework.model.player.AbstractAI;
|
||||||
import org.toop.game.reversi.Reversi;
|
import org.toop.framework.gameFramework.model.player.Player;
|
||||||
import org.toop.game.reversi.ReversiAI;
|
import org.toop.game.games.reversi.ReversiAIR;
|
||||||
import org.toop.game.reversi.ReversiAIML;
|
import org.toop.game.games.reversi.ReversiR;
|
||||||
import org.toop.game.reversi.ReversiAISimple;
|
import org.toop.game.games.reversi.ReversiAIML;
|
||||||
|
import org.toop.game.games.reversi.ReversiAISimple;
|
||||||
|
|
||||||
import java.io.File;
|
import java.io.File;
|
||||||
import java.io.IOException;
|
import java.io.IOException;
|
||||||
@@ -33,11 +34,10 @@ public class NeuralNetwork {
|
|||||||
|
|
||||||
private MultiLayerConfiguration conf;
|
private MultiLayerConfiguration conf;
|
||||||
private MultiLayerNetwork model;
|
private MultiLayerNetwork model;
|
||||||
private AI<Reversi> opponentAI;
|
private AbstractAI<ReversiR> opponentAI;
|
||||||
private ReversiAI reversiAI = new ReversiAI();
|
private AbstractAI<ReversiR> opponentRand = new ReversiAIR();
|
||||||
private AI<Reversi> opponentRand = new ReversiAI();
|
private AbstractAI<ReversiR> opponentSimple = new ReversiAISimple();
|
||||||
private AI<Reversi> opponentSimple = new ReversiAISimple();
|
private AbstractAI<ReversiR> opponentAIML = new ReversiAIML();
|
||||||
private AI<Reversi> opponentAIML = new ReversiAIML();
|
|
||||||
|
|
||||||
|
|
||||||
public NeuralNetwork() {}
|
public NeuralNetwork() {}
|
||||||
@@ -89,27 +89,27 @@ public class NeuralNetwork {
|
|||||||
}
|
}
|
||||||
|
|
||||||
public void trainingLoop(){
|
public void trainingLoop(){
|
||||||
int totalGames = 50000;
|
int totalGames = 5000;
|
||||||
double epsilon = 0.05;
|
double epsilon = 0.05;
|
||||||
|
|
||||||
long start = System.nanoTime();
|
long start = System.nanoTime();
|
||||||
|
|
||||||
for (int game = 0; game<totalGames; game++){
|
for (int game = 0; game<totalGames; game++){
|
||||||
char modelPlayer = random()<0.5?'B':'W';
|
char modelPlayer = random()<0.5?'B':'W';
|
||||||
Reversi reversi = new Reversi();
|
ReversiR reversi = new ReversiR(new Player[2]);
|
||||||
opponentAI = getOpponentAI();
|
opponentAI = getOpponentAI();
|
||||||
List<StateAction> gameHistory = new ArrayList<>();
|
List<StateAction> gameHistory = new ArrayList<>();
|
||||||
GameState state = GameState.NORMAL;
|
PlayResult state = new PlayResult(GameState.NORMAL,reversi.getCurrentTurn());
|
||||||
|
|
||||||
double reward = 0;
|
double reward = 0;
|
||||||
|
|
||||||
while (state != GameState.DRAW && state != GameState.WIN){
|
while (state.state() != GameState.DRAW && state.state() != GameState.WIN){
|
||||||
char curr = reversi.getCurrentPlayer();
|
int curr = reversi.getCurrentTurn();
|
||||||
Move move;
|
int move;
|
||||||
if (curr == modelPlayer) {
|
if (curr == modelPlayer) {
|
||||||
int[] input = reversi.getBoardInt();
|
int[] input = reversi.getBoard();
|
||||||
if (Math.random() < epsilon) {
|
if (Math.random() < epsilon) {
|
||||||
Move[] moves = reversi.getLegalMoves();
|
int[] moves = reversi.getLegalMoves();
|
||||||
move = moves[(int) (Math.random() * moves.length - .5f)];
|
move = moves[(int) (Math.random() * moves.length - .5f)];
|
||||||
} else {
|
} else {
|
||||||
INDArray boardInput = Nd4j.create(new int[][]{input});
|
INDArray boardInput = Nd4j.create(new int[][]{input});
|
||||||
@@ -117,16 +117,16 @@ public class NeuralNetwork {
|
|||||||
|
|
||||||
int location = pickLegalMove(prediction, reversi);
|
int location = pickLegalMove(prediction, reversi);
|
||||||
gameHistory.add(new StateAction(input, location));
|
gameHistory.add(new StateAction(input, location));
|
||||||
move = new Move(location, reversi.getCurrentPlayer());
|
move = location;
|
||||||
}
|
}
|
||||||
}else{
|
}else{
|
||||||
move = opponentAI.findBestMove(reversi,5);
|
move = opponentAI.getMove(reversi);
|
||||||
}
|
}
|
||||||
state = reversi.play(move);
|
state = reversi.play(move);
|
||||||
}
|
}
|
||||||
|
|
||||||
//IO.println(model.params());
|
//IO.println(model.params());
|
||||||
Reversi.Score score = reversi.getScore();
|
ReversiR.Score score = reversi.getScore();
|
||||||
int scoreDif = abs(score.player1Score() - score.player2Score());
|
int scoreDif = abs(score.player1Score() - score.player2Score());
|
||||||
if (score.player1Score() > score.player2Score()){
|
if (score.player1Score() > score.player2Score()){
|
||||||
reward = 1 + ((scoreDif / 64.0) * 0.5);
|
reward = 1 + ((scoreDif / 64.0) * 0.5);
|
||||||
@@ -155,29 +155,26 @@ public class NeuralNetwork {
|
|||||||
IO.println((end-start));
|
IO.println((end-start));
|
||||||
}
|
}
|
||||||
|
|
||||||
private boolean isInCorner(Move move){
|
|
||||||
return move.position() == 0 || move.position() == 7 || move.position() == 56 || move.position() == 63;
|
|
||||||
}
|
|
||||||
|
|
||||||
private int pickLegalMove(INDArray prediction, Reversi reversi){
|
private int pickLegalMove(INDArray prediction, ReversiR reversi){
|
||||||
double[] probs = prediction.toDoubleVector();
|
double[] probs = prediction.toDoubleVector();
|
||||||
Move[] legalMoves = reversi.getLegalMoves();
|
int[] legalMoves = reversi.getLegalMoves();
|
||||||
|
|
||||||
if (legalMoves.length == 0) return -1;
|
if (legalMoves.length == 0) return -1;
|
||||||
|
|
||||||
int bestMove = legalMoves[0].position();
|
int bestMove = legalMoves[0];
|
||||||
double bestVal = probs[bestMove];
|
double bestVal = probs[bestMove];
|
||||||
|
|
||||||
for (Move move : legalMoves){
|
for (int move : legalMoves){
|
||||||
if (probs[move.position()] > bestVal){
|
if (probs[move] > bestVal){
|
||||||
bestMove = move.position();
|
bestMove = move;
|
||||||
bestVal = probs[bestMove];
|
bestVal = probs[bestMove];
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
return bestMove;
|
return bestMove;
|
||||||
}
|
}
|
||||||
|
|
||||||
private AI<Reversi> getOpponentAI(){
|
private AbstractAI<ReversiR> getOpponentAI(){
|
||||||
return switch ((int) (Math.random() * 4)) {
|
return switch ((int) (Math.random() * 4)) {
|
||||||
case 0 -> opponentRand;
|
case 0 -> opponentRand;
|
||||||
case 1 -> opponentSimple;
|
case 1 -> opponentSimple;
|
||||||
@@ -1,4 +1,4 @@
|
|||||||
package org.toop.framework.machinelearning;
|
package org.toop.game.machinelearning;
|
||||||
|
|
||||||
public class StateAction {
|
public class StateAction {
|
||||||
int[] state;
|
int[] state;
|
||||||
@@ -1,301 +0,0 @@
|
|||||||
package org.toop.game.reversi;
|
|
||||||
|
|
||||||
import org.toop.game.TurnBasedGame;
|
|
||||||
import org.toop.game.enumerators.GameState;
|
|
||||||
import org.toop.game.records.Move;
|
|
||||||
|
|
||||||
import java.awt.*;
|
|
||||||
import java.util.ArrayList;
|
|
||||||
import java.util.Arrays;
|
|
||||||
import java.util.HashSet;
|
|
||||||
import java.util.Set;
|
|
||||||
|
|
||||||
|
|
||||||
public final class Reversi extends TurnBasedGame {
|
|
||||||
private int movesTaken;
|
|
||||||
private Set<Point> filledCells = new HashSet<>();
|
|
||||||
private Move[] mostRecentlyFlippedPieces;
|
|
||||||
private char[][] cachedBoard;
|
|
||||||
|
|
||||||
public record Score(int player1Score, int player2Score) {}
|
|
||||||
|
|
||||||
public Reversi() {
|
|
||||||
super(8, 8, 2);
|
|
||||||
addStartPieces();
|
|
||||||
}
|
|
||||||
|
|
||||||
public Reversi(Reversi other) {
|
|
||||||
super(other);
|
|
||||||
this.movesTaken = other.movesTaken;
|
|
||||||
this.filledCells = other.filledCells;
|
|
||||||
this.mostRecentlyFlippedPieces = other.mostRecentlyFlippedPieces;
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
private void addStartPieces() {
|
|
||||||
this.setBoard(new Move(27, 'W'));
|
|
||||||
this.setBoard(new Move(28, 'B'));
|
|
||||||
this.setBoard(new Move(35, 'B'));
|
|
||||||
this.setBoard(new Move(36, 'W'));
|
|
||||||
updateFilledCellsSet();
|
|
||||||
cachedBoard = makeBoardAGrid();
|
|
||||||
}
|
|
||||||
private void updateFilledCellsSet() {
|
|
||||||
for (int i = 0; i < 64; i++) {
|
|
||||||
if (this.getBoard()[i] == 'W' || this.getBoard()[i] == 'B') {
|
|
||||||
filledCells.add(new Point(i % this.getColumnSize(), i / this.getRowSize()));
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
@Override
|
|
||||||
public Move[] getLegalMoves() {
|
|
||||||
final ArrayList<Move> legalMoves = new ArrayList<>();
|
|
||||||
char[][] boardGrid = cachedBoard;
|
|
||||||
char currentPlayer = (this.getCurrentTurn()==0) ? 'B' : 'W';
|
|
||||||
char opponent = (currentPlayer=='W') ? 'B' : 'W';
|
|
||||||
|
|
||||||
Set<Point> adjCell = getAdjacentCells(boardGrid, opponent);
|
|
||||||
for (Point point : adjCell){
|
|
||||||
Move[] moves = getFlipsForPotentialMove(point, currentPlayer, opponent, boardGrid);
|
|
||||||
int score = moves.length;
|
|
||||||
if (score > 0){
|
|
||||||
legalMoves.add(new Move(point.x + point.y * this.getRowSize(), currentPlayer));
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return legalMoves.toArray(new Move[0]);
|
|
||||||
}
|
|
||||||
|
|
||||||
private Set<Point> getAdjacentCells(char[][] boardGrid, char opponent) {
|
|
||||||
Set<Point> possibleCells = new HashSet<>();
|
|
||||||
for (Point point : filledCells) { //for every filled cell
|
|
||||||
if (boardGrid[point.x][point.y] == opponent) {
|
|
||||||
for (int deltaColumn = -1; deltaColumn <= 1; deltaColumn++) { //check adjacent cells
|
|
||||||
for (int deltaRow = -1; deltaRow <= 1; deltaRow++) { //orthogonally and diagonally
|
|
||||||
int newX = point.x + deltaColumn, newY = point.y + deltaRow;
|
|
||||||
if (deltaColumn == 0 && deltaRow == 0 //continue if out of bounds
|
|
||||||
|| !isOnBoard(newX, newY)) {
|
|
||||||
continue;
|
|
||||||
}
|
|
||||||
if (boardGrid[newY][newX] == EMPTY) { //check if the cell is empty
|
|
||||||
possibleCells.add(new Point(newX, newY)); //and then add it to the set of possible moves
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return possibleCells;
|
|
||||||
}
|
|
||||||
|
|
||||||
public Move[] getFlipsForPotentialMove(Point point, char currentPlayer, char opponent, char[][] boardGrid) {
|
|
||||||
final ArrayList<Move> movesToFlip = new ArrayList<>();
|
|
||||||
for (int deltaColumn = -1; deltaColumn <= 1; deltaColumn++) { //for all directions
|
|
||||||
for (int deltaRow = -1; deltaRow <= 1; deltaRow++) {
|
|
||||||
if (deltaColumn == 0 && deltaRow == 0){
|
|
||||||
continue;
|
|
||||||
}
|
|
||||||
Move[] moves = getFlipsInDirection(point, boardGrid, currentPlayer, opponent, deltaColumn, deltaRow);
|
|
||||||
if (moves != null) { //getFlipsInDirection
|
|
||||||
movesToFlip.addAll(Arrays.asList(moves));
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return movesToFlip.toArray(new Move[0]);
|
|
||||||
}
|
|
||||||
|
|
||||||
public Move[] getFlipsForPotentialMove(Move move) {
|
|
||||||
char curr = getCurrentPlayer();
|
|
||||||
char opp = getOpponent(curr);
|
|
||||||
Point point = new Point(move.position() % this.getRowSize(), move.position() / this.getColumnSize());
|
|
||||||
return getFlipsForPotentialMove(point, curr, opp, cachedBoard);
|
|
||||||
}
|
|
||||||
|
|
||||||
private Move[] getFlipsInDirection(Point point, char[][] boardGrid, char currentPlayer, char opponent, int dirX, int dirY) {
|
|
||||||
final ArrayList<Move> movesToFlip = new ArrayList<>();
|
|
||||||
int x = point.x + dirX;
|
|
||||||
int y = point.y + dirY;
|
|
||||||
|
|
||||||
if (!isOnBoard(x, y) || boardGrid[y][x] != opponent) { //there must first be an opponents tile
|
|
||||||
return null;
|
|
||||||
}
|
|
||||||
|
|
||||||
while (isOnBoard(x, y) && boardGrid[y][x] == opponent) { //count the opponents tiles in this direction
|
|
||||||
|
|
||||||
movesToFlip.add(new Move(x+y*this.getRowSize(), currentPlayer));
|
|
||||||
x += dirX;
|
|
||||||
y += dirY;
|
|
||||||
}
|
|
||||||
if (isOnBoard(x, y) && boardGrid[y][x] == currentPlayer) {
|
|
||||||
return movesToFlip.toArray(new Move[0]); //only return the count if last tile is ours
|
|
||||||
}
|
|
||||||
return null;
|
|
||||||
}
|
|
||||||
|
|
||||||
private boolean isOnBoard(int x, int y) {
|
|
||||||
return x >= 0 && x < this.getColumnSize() && y >= 0 && y < this.getRowSize();
|
|
||||||
}
|
|
||||||
|
|
||||||
public char[][] makeBoardAGrid() {
|
|
||||||
char[][] boardGrid = new char[this.getRowSize()][this.getColumnSize()];
|
|
||||||
for (int i = 0; i < 64; i++) {
|
|
||||||
boardGrid[i / this.getRowSize()][i % this.getColumnSize()] = this.getBoard()[i]; //boardGrid[y -> row] [x -> column]
|
|
||||||
}
|
|
||||||
return boardGrid;
|
|
||||||
}
|
|
||||||
|
|
||||||
@Override
|
|
||||||
public GameState play(Move move) {
|
|
||||||
if (cachedBoard == null) {
|
|
||||||
cachedBoard = makeBoardAGrid();
|
|
||||||
}
|
|
||||||
Move[] legalMoves = getLegalMoves();
|
|
||||||
boolean moveIsLegal = false;
|
|
||||||
for (Move legalMove : legalMoves) { //check if the move is legal
|
|
||||||
if (move.equals(legalMove)) {
|
|
||||||
moveIsLegal = true;
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
if (!moveIsLegal) {
|
|
||||||
return null;
|
|
||||||
}
|
|
||||||
|
|
||||||
Move[] moves = sortMovesFromCenter(getFlipsForPotentialMove(new Point(move.position()%this.getColumnSize(),move.position()/this.getRowSize()), move.value(),move.value() == 'B'? 'W': 'B',makeBoardAGrid()),move);
|
|
||||||
mostRecentlyFlippedPieces = moves;
|
|
||||||
this.setBoard(move); //place the move on the board
|
|
||||||
for (Move m : moves) {
|
|
||||||
this.setBoard(m); //flip the correct pieces on the board
|
|
||||||
}
|
|
||||||
filledCells.add(new Point(move.position() % this.getRowSize(), move.position() / this.getColumnSize()));
|
|
||||||
cachedBoard = makeBoardAGrid();
|
|
||||||
nextTurn();
|
|
||||||
if (getLegalMoves().length == 0) { //skip the players turn when there are no legal moves
|
|
||||||
skipMyTurn();
|
|
||||||
if (getLegalMoves().length > 0) {
|
|
||||||
return GameState.TURN_SKIPPED;
|
|
||||||
}
|
|
||||||
else { //end the game when neither player has a legal move
|
|
||||||
Score score = getScore();
|
|
||||||
if (score.player1Score() == score.player2Score()) {
|
|
||||||
return GameState.DRAW;
|
|
||||||
}
|
|
||||||
else {
|
|
||||||
return GameState.WIN;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return GameState.NORMAL;
|
|
||||||
}
|
|
||||||
|
|
||||||
private void skipMyTurn(){
|
|
||||||
//IO.println("TURN " + getCurrentPlayer() + " SKIPPED");
|
|
||||||
//TODO: notify user that a turn has been skipped
|
|
||||||
nextTurn();
|
|
||||||
}
|
|
||||||
|
|
||||||
public char getCurrentPlayer() {
|
|
||||||
if (this.getCurrentTurn() == 0){
|
|
||||||
return 'B';
|
|
||||||
}
|
|
||||||
else {
|
|
||||||
return 'W';
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
private char getOpponent(char currentPlayer){
|
|
||||||
if (currentPlayer == 'B') {
|
|
||||||
return 'W';
|
|
||||||
}
|
|
||||||
else {
|
|
||||||
return 'B';
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
public Score getScore(){
|
|
||||||
int player1Score = 0, player2Score = 0;
|
|
||||||
for (int count = 0; count < this.getRowSize() * this.getColumnSize(); count++) {
|
|
||||||
if (this.getBoard()[count] == 'B') {
|
|
||||||
player1Score += 1;
|
|
||||||
}
|
|
||||||
if (this.getBoard()[count] == 'W') {
|
|
||||||
player2Score += 1;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return new Score(player1Score, player2Score);
|
|
||||||
}
|
|
||||||
|
|
||||||
public boolean isGameOver(){
|
|
||||||
Move[] legalMovesW = getLegalMoves();
|
|
||||||
nextTurn();
|
|
||||||
Move[] legalMovesB = getLegalMoves();
|
|
||||||
nextTurn();
|
|
||||||
if (legalMovesW.length + legalMovesB.length == 0) {
|
|
||||||
return true;
|
|
||||||
}
|
|
||||||
return false;
|
|
||||||
}
|
|
||||||
|
|
||||||
public int getWinner(){
|
|
||||||
if (!isGameOver()) {
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
Score score = getScore();
|
|
||||||
if (score.player1Score() > score.player2Score()) {
|
|
||||||
return 1;
|
|
||||||
}
|
|
||||||
else if (score.player1Score() < score.player2Score()) {
|
|
||||||
return 2;
|
|
||||||
}
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
private Move[] sortMovesFromCenter(Move[] moves, Move center) { //sorts the pieces to be flipped for animation purposes
|
|
||||||
int centerX = center.position()%this.getColumnSize();
|
|
||||||
int centerY = center.position()/this.getRowSize();
|
|
||||||
Arrays.sort(moves, (a, b) -> {
|
|
||||||
int dxA = a.position()%this.getColumnSize() - centerX;
|
|
||||||
int dyA = a.position()/this.getRowSize() - centerY;
|
|
||||||
int dxB = b.position()%this.getColumnSize() - centerX;
|
|
||||||
int dyB = b.position()/this.getRowSize() - centerY;
|
|
||||||
|
|
||||||
int distA = dxA * dxA + dyA * dyA;
|
|
||||||
int distB = dxB * dxB + dyB * dyB;
|
|
||||||
|
|
||||||
return Integer.compare(distA, distB);
|
|
||||||
});
|
|
||||||
return moves;
|
|
||||||
}
|
|
||||||
public Move[] getMostRecentlyFlippedPieces() {
|
|
||||||
return mostRecentlyFlippedPieces;
|
|
||||||
}
|
|
||||||
|
|
||||||
public int[] getBoardInt(){
|
|
||||||
char[] input = getBoard();
|
|
||||||
int[] result = new int[input.length];
|
|
||||||
for (int i = 0; i < input.length; i++) {
|
|
||||||
switch (input[i]) {
|
|
||||||
case 'W':
|
|
||||||
result[i] = -1;
|
|
||||||
break;
|
|
||||||
case 'B':
|
|
||||||
result[i] = 1;
|
|
||||||
break;
|
|
||||||
case ' ':
|
|
||||||
default:
|
|
||||||
result[i] = 0;
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return result;
|
|
||||||
}
|
|
||||||
|
|
||||||
public Point moveToPoint(Move move){
|
|
||||||
return new Point(move.position()%this.getColumnSize(),move.position()/this.getRowSize());
|
|
||||||
}
|
|
||||||
|
|
||||||
public void printBoard(){
|
|
||||||
for (int row = 0; row < this.getRowSize(); row++) {
|
|
||||||
IO.println(Arrays.toString(cachedBoard[row]));
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@@ -1,15 +0,0 @@
|
|||||||
package org.toop.game.reversi;
|
|
||||||
|
|
||||||
import org.toop.game.AI;
|
|
||||||
import org.toop.game.records.Move;
|
|
||||||
|
|
||||||
public final class ReversiAI extends AI<Reversi> {
|
|
||||||
|
|
||||||
@Override
|
|
||||||
public Move findBestMove(Reversi game, int depth) {
|
|
||||||
Move[] moves = game.getLegalMoves();
|
|
||||||
int inty = (int)(Math.random() * moves.length-.5f);
|
|
||||||
if (moves.length == 0) return null;
|
|
||||||
return moves[inty];
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@@ -1,31 +1,40 @@
|
|||||||
|
/*//todo fix this mess
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
package org.toop.game.tictactoe;
|
package org.toop.game.tictactoe;
|
||||||
|
|
||||||
import java.util.*;
|
import java.util.*;
|
||||||
|
|
||||||
import org.junit.jupiter.api.BeforeEach;
|
import org.junit.jupiter.api.BeforeEach;
|
||||||
import org.junit.jupiter.api.Test;
|
import org.junit.jupiter.api.Test;
|
||||||
|
import org.toop.framework.gameFramework.model.player.AbstractAI;
|
||||||
|
import org.toop.framework.gameFramework.model.player.Player;
|
||||||
import org.toop.game.AI;
|
import org.toop.game.AI;
|
||||||
import org.toop.game.enumerators.GameState;
|
import org.toop.game.enumerators.GameState;
|
||||||
|
import org.toop.game.games.reversi.ReversiAIR;
|
||||||
|
import org.toop.game.games.reversi.ReversiR;
|
||||||
import org.toop.game.records.Move;
|
import org.toop.game.records.Move;
|
||||||
import org.toop.game.reversi.Reversi;
|
import org.toop.game.reversi.Reversi;
|
||||||
import org.toop.game.reversi.ReversiAI;
|
import org.toop.game.reversi.ReversiAI;
|
||||||
import org.toop.game.reversi.ReversiAIML;
|
import org.toop.game.games.reversi.ReversiAIML;
|
||||||
import org.toop.game.reversi.ReversiAISimple;
|
import org.toop.game.games.reversi.ReversiAISimple;
|
||||||
|
|
||||||
import static org.junit.jupiter.api.Assertions.*;
|
import static org.junit.jupiter.api.Assertions.*;
|
||||||
|
|
||||||
class ReversiTest {
|
class ReversiTest {
|
||||||
private Reversi game;
|
private ReversiR game;
|
||||||
private ReversiAI ai;
|
private ReversiAIR ai;
|
||||||
private ReversiAIML aiml;
|
private ReversiAIML aiml;
|
||||||
private ReversiAISimple aiSimple;
|
private ReversiAISimple aiSimple;
|
||||||
private AI<Reversi> player1;
|
private AbstractAI<ReversiR> player1;
|
||||||
private AI<Reversi> player2;
|
private AbstractAI<ReversiR> player2;
|
||||||
|
private Player[] players = new Player[2];
|
||||||
|
|
||||||
@BeforeEach
|
@BeforeEach
|
||||||
void setup() {
|
void setup() {
|
||||||
game = new Reversi();
|
game = new ReversiR(players);
|
||||||
ai = new ReversiAI();
|
ai = new ReversiAIR();
|
||||||
aiml = new ReversiAIML();
|
aiml = new ReversiAIML();
|
||||||
aiSimple = new ReversiAISimple();
|
aiSimple = new ReversiAISimple();
|
||||||
|
|
||||||
@@ -231,7 +240,7 @@ class ReversiTest {
|
|||||||
int draws = 0;
|
int draws = 0;
|
||||||
List<Integer> moves = new ArrayList<>();
|
List<Integer> moves = new ArrayList<>();
|
||||||
for (int i = 0; i < totalGames; i++) {
|
for (int i = 0; i < totalGames; i++) {
|
||||||
game = new Reversi();
|
game = new ReversiR();
|
||||||
while (!game.isGameOver()) {
|
while (!game.isGameOver()) {
|
||||||
char curr = game.getCurrentPlayer();
|
char curr = game.getCurrentPlayer();
|
||||||
Move move;
|
Move move;
|
||||||
@@ -258,4 +267,6 @@ class ReversiTest {
|
|||||||
}
|
}
|
||||||
IO.println("p1 winrate: " + p1wins + "/" + totalGames + " = " + (double) p1wins / totalGames + "\np2wins: " + p2wins + " draws: " + draws);
|
IO.println("p1 winrate: " + p1wins + "/" + totalGames + " = " + (double) p1wins / totalGames + "\np2wins: " + p2wins + " draws: " + draws);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
*/
|
||||||
Reference in New Issue
Block a user