不看后悔（java象棋源码）java象棋算法思路，JAVA 实现《中国象棋》游戏（小虚竹），中国象棋打谱软件java，

@Slf4jpublic class BoardPanel extends JPanel implements LambdaMouseListener {/*** 用于标记棋盘走棋痕迹*/private final transient TraceMarker traceMarker;/*** 当前走棋开始坐标位置对应棋子*/private transient ChessPiece curFromPiece;/*** 场景*/private transient Situation situation;/*** Create the panel.*/public BoardPanel() {setBorder(new EmptyBorder(5, 5, 5, 5));setLayout(null);// 初始化标记符traceMarker = new TraceMarker(BoardPanel.this);// 添加鼠标事件addMouseListener(this);}/*** 更新标记*/public void updateMark(Place from, Place to) {// 更新标记curFromPiece = null;// 更改标记traceMarker.endedStep(from, to);}/*** 初始化所有标记*/public void initMark() {traceMarker.initMarker();}/*** 添加棋子*/public void init(Situation situation) {this.situation = situation;// 移除所有组件this.removeAll();// 添加棋子situation.getPieceList().forEach(it -> add(it.getComp()));situation.getSituationRecord().getEatenPieceList().forEach(it -> add(it.getComp()));// 初始化标记符traceMarker.initMarker();repaint();}/*** @param e 鼠标按压事件对象*/@Overridepublic void mouseReleased(MouseEvent e) {// 位置Place pointerPlace = ChessDefined.convertLocationToPlace(e.getPoint());if (pointerPlace == null) {return;}if (situation.winner() != null) {log.warn("已经存在胜利者: {}, 无法走棋", situation.winner());return;}// 当前走棋方@NonNull Part pointerPart = situation.getNextPart();// 当前焦点棋子ChessPiece pointerPiece = situation.getChessPiece(pointerPlace);// 通过当前方和当前位置判断是否可以走棋// step: formif (curFromPiece == null) {// 当前焦点位置有棋子且是本方棋子if (pointerPiece != null && pointerPiece.piece.part == pointerPart) {// 本方棋子, 同时是from指向curFromPiece = pointerPiece;traceMarker.setMarkFromPlace(pointerPlace);// 获取toListMyList<Place> list = curFromPiece.piece.role.find(new AnalysisBean(situation.generatePieces()), pointerPart, pointerPlace);traceMarker.showMarkPlace(list);ChessAudio.CLICK_FROM.play();log.info("true -> 当前焦点位置有棋子且是本方棋子");final ListPool listPool = ListPool.localPool();listPool.addListToPool(list);return;}log.warn("warning -> from 焦点指示错误");return;}if (pointerPlace.equals(curFromPiece.getPlace())) {log.warn("false -> from == to");return;}// 当前焦点位置有棋子且是本方棋子if (pointerPiece != null && pointerPiece.piece.part == pointerPart) {assert curFromPiece.piece.part == pointerPart : "当前焦点位置有棋子且是本方棋子 之前指向了对方棋子";// 更新 curFromPiececurFromPiece = pointerPiece;traceMarker.setMarkFromPlace(pointerPlace);MyList<Place> list = curFromPiece.piece.role.find(new AnalysisBean(situation.generatePieces()), pointerPart, pointerPlace);traceMarker.showMarkPlace(list);ChessAudio.CLICK_FROM.play();log.info("true -> 更新 curFromPiece");ListPool.localPool().addListToPool(list);return;}final StepBean stepBean = StepBean.of(curFromPiece.getPlace(), pointerPlace);// 如果不符合规则则直接返回final Piece[][] pieces = situation.generatePieces();if (!curFromPiece.piece.role.rule.check(pieces, pointerPart, stepBean.from, stepBean.to)) {// 如果当前指向棋子是本方棋子log.warn("不符合走棋规则");return;}// 如果达成长拦或者长捉, 则返回final StepBean forbidStepBean = situation.getForbidStepBean();if (forbidStepBean != null && forbidStepBean.from == stepBean.from && forbidStepBean.to == stepBean.to) {ChessAudio.MAN_MOV_ERROR.play();log.warn("长拦或长捉");return;}AnalysisBean analysisBean = new AnalysisBean(pieces);// 如果走棋后, 导致两个 BOSS 对面, 则返回if (!analysisBean.isBossF2FAfterStep(curFromPiece.piece, stepBean.from, stepBean.to)) {ChessAudio.MAN_MOV_ERROR.play();log.warn("BOSS面对面");return;}/* 模拟走一步棋, 之后再计算对方再走一步是否能够吃掉本方的 boss */if (analysisBean.simulateOneStep(stepBean, bean -> bean.canEatBossAfterOneAiStep(Part.getOpposite(pointerPart)))) {ChessAudio.MAN_MOV_ERROR.play();log.warn("BOSS 危险");if (!Application.config().isActiveWhenBeCheck()) {return;}}// 当前棋子无棋子或者为对方棋子, 且符合规则, 可以走棋Object[] objects = new Object[]{stepBean.from, stepBean.to, PlayerType.PEOPLE};final boolean sendSuccess = Application.context().getCommandExecutor().sendCommandWhenNotRun(CommandExecutor.CommandType.LocationPiece, objects);if (!sendSuccess) {log.warn("命令未发送成功: {} ==> {}", CommandExecutor.CommandType.LocationPiece, Arrays.toString(objects));}}@Overridepublic void paintComponent(Graphics g) {super.paintComponent(g);Image img = ChessImage.CHESS_BOARD.getImage();int imgWidth = img.getWidth(this);int imgHeight = img.getHeight(this);// 获得图片的宽度与高度int fWidth = getWidth();int fHeight = getHeight();// 获得窗口的宽度与高度int x = (fWidth - imgWidth) / 2;int y = (fHeight - imgHeight) / 2;// 520 576 514 567log.debug(String.format("%s,%s,%s,%s,%s,%s", imgWidth, imgHeight, fWidth, fHeight, x, y));g.drawImage(img, 0, 0, null);}}

@Slf4jpublic class CommandExecutor {/*** 异步调用线程, 来处理走棋命令*/private final CtrlLoopThreadComp ctrlLoopThreadComp;private final BoardPanel boardPanel;/*** 是否持续运行标记*/private volatile boolean sustain;public CommandExecutor(BoardPanel boardPanel) {this.boardPanel = boardPanel;this.ctrlLoopThreadComp = CtrlLoopThreadComp.ofRunnable(this::loop).setName("CommandExecutor").catchFun(CtrlLoopThreadComp.CATCH_FUNCTION_CONTINUE);}/*** 下一步骤命令*/private CommandType nextCommand;/*** 下一步骤命令的参数*/private Object nextParamObj;private volatile boolean isRun;/*** @param commandType 命令类型*/public void sendCommand(@NonNull CommandType commandType) {sendCommand(commandType, null);}/*** @param commandType 命令类型* @param paramObj 命令参数*/public synchronized void sendCommand(@NonNull CommandType commandType, Object paramObj) {this.nextCommand = commandType;this.nextParamObj = paramObj;sustain = false;this.ctrlLoopThreadComp.startOrWake();}/*** 只有在 线程没有运行的情况下, 才能添加成功** @param commandType 命令类型* @param paramObj 命令参数* @return 是否添加成功*/public synchronized boolean sendCommandWhenNotRun(@NonNull CommandType commandType, Object paramObj) {if (isRun) {return false;}sendCommand(commandType, paramObj);return true;}private void loop() {final CommandType command;final Object paramObj;synchronized (this) {command = this.nextCommand;paramObj = this.nextParamObj;this.nextCommand = null;this.nextParamObj = null;}if (command != null) {isRun = true;try {log.debug("处理事件[{}] start", command.getLabel());consumerCommand(command, paramObj);log.debug("处理事件[{}] end ", command.getLabel());} catch (Exception e) {log.error("执行命令[{}]发生异常", command.getLabel(), e);new Thread(() -> JOptionPane.showMessageDialog(boardPanel, e.getMessage(), e.toString(), JOptionPane.ERROR_MESSAGE)).start();}} else {this.ctrlLoopThreadComp.pause();isRun = false;}}/*** 运行*/private void consumerCommand(final CommandType commandType, Object paramObj) {switch (commandType) {case SuspendCallBackOrAiRun:break;case CallBackOneTime:Application.context().rollbackOneStep();break;case AiRunOneTime:if (Application.context().aiRunOneTime() != null) {log.debug("已经决出胜方!");}break;case SustainCallBack:sustain = true;while (sustain) {if (!Application.context().rollbackOneStep()) {sustain = false;break;}Throws.con(Application.config().getComIntervalTime(), Thread::sleep).logThrowable();}break;case SustainAiRun:sustain = true;while (sustain) {if (Application.context().aiRunOneTime() != null) {log.debug("已经决出胜方, AI执行暂停!");sustain = false;break;}Throws.con(Application.config().getComIntervalTime(), Thread::sleep).logThrowable();}break;case SustainAiRunIfNextIsAi:sustain = true;while (sustain) {// 如果下一步棋手不是 AI, 则暂停if (!PlayerType.COM.equals(Application.config().getPlayerType(Application.context().getSituation().getNextPart()))) {sustain = false;log.debug("下一步棋手不是 AI, 暂停!");} else if (Application.context().aiRunOneTime() != null) {log.debug("已经决出胜方, AI执行暂停!");sustain = false;} else {Throws.con(Application.config().getComIntervalTime(), Thread::sleep).logThrowable();}}break;case LocationPiece:final Object[] params = (Object[]) paramObj;Place from = (Place) params[0];Place to = (Place) params[1];PlayerType type = (PlayerType) params[2];Application.context().locatePiece(from, to, type);sendCommand(CommandExecutor.CommandType.SustainAiRunIfNextIsAi);break;default:throw new ShouldNotHappenException("未处理的命令: " + commandType);}}/*** 命令支持枚举(以下命令应当使用同一个线程运行, 一个事件结束之后, 另一个事件才能开始运行.)*/@SuppressWarnings("java:S115")public enum CommandType {SuspendCallBackOrAiRun("停止撤销|AI计算"),CallBackOneTime("撤销一步"),SustainCallBack("持续撤销"),AiRunOneTime("AI计算一步"),SustainAiRun("AI持续运行"),SustainAiRunIfNextIsAi("COM角色运行"),LocationPiece("ui落子命令");@Getterprivate final String label;CommandType(String label) {this.label = label;}}}

@NoArgsConstructor(access = AccessLevel.PRIVATE)@Slf4jpublic class AlphaBeta {private static final int MAX = 100_000_000;/*** 这里要保证 Min + Max = 0, 哪怕是微不足道的差距都可能导致发生错误*/private static final int MIN = -MAX;/*** 根据棋子数量, 动态调整搜索深度** @param pieceNum 棋子数量* @return 调整搜索深度差值*/public static int searchDeepSuit(final int pieceNum) {// 根据棋子数量, 动态调整搜索深度if (pieceNum > 20) {return -2;} else if (pieceNum <= 4) {return 4;} else if (pieceNum <= 8) {return 2;}return 0;}/*** 生成待选的列表，就是可以下子的空位, 如果 deep > 2 则对搜索结果进行排序.** @param analysisBean 棋盘分析对象* @param curPart 当前走棋方* @param deep 搜索深度* @return 可以下子的空位集合*/private static MyList<StepBean> geneNestStepPlaces(final AnalysisBean analysisBean, final Part curPart, final int deep) {final Piece[][] pieces = analysisBean.pieces;// 是否杀棋MyList<StepBean> stepBeanList = ListPool.localPool().getAStepBeanList();for (int x = 0; x < ChessDefined.RANGE_X; x++) {for (int y = 0; y < ChessDefined.RANGE_Y; y++) {final Piece fromPiece = pieces[x][y];if (fromPiece != null && fromPiece.part == curPart) {final Place from = Place.of(x, y);// TO DO 考虑下此处添加至集合的做法 在计算时 是否有优化空间.final MyList<Place> list = fromPiece.role.find(analysisBean, curPart, from);if (list.isEmpty()) {ListPool.localPool().addListToPool(list);continue;}final Object[] elementData = list.eleTemplateDate();for (int i = 0, len = list.size(); i < len; i++) {stepBeanList.add(StepBean.of(from, (Place) elementData[i]));}ListPool.localPool().addListToPool(list);}}}// 是否排序, 如果搜索深度大于2, 则对结果进行排序// 排序后的结果, 进入极大极小值搜索算法时, 容易被剪枝.if (deep > 2) {orderStep(analysisBean, stepBeanList, curPart);}return stepBeanList;}/*** 对 空位列表 进行排序, 排序后的空位列表, 进入极大极小值搜索算法时, 容易被剪枝.** @param analysisBean 棋盘分析对象* @param stepBeanList 可以下子的空位列表* @param curPart 当前走棋方*/private static void orderStep(final AnalysisBean analysisBean, final MyList<StepBean> stepBeanList, final Part curPart) {final Piece[][] srcPieces = analysisBean.pieces;// 进入循环之前计算好循环内使用常量MyList<DoubleBean<Integer, StepBean>> bestPlace = ListPool.localPool().getADoubleBeanList();// 对方棋手final Part oppositeCurPart = Part.getOpposite(curPart);int best = MIN;final Object[] objects = stepBeanList.eleTemplateDate();for (int i = 0; i < stepBeanList.size(); i++) {final StepBean item = (StepBean) objects[i];final Place to = item.to;// 备份final Piece eatenPiece = srcPieces[to.x][to.y];int score;// 判断是否胜利if (eatenPiece != null && eatenPiece.role == Role.BOSS) {score = MAX;} else {// 走棋final int invScr = analysisBean.goForward(item.from, to, eatenPiece);DebugInfo.incrementAlphaBetaOrderTime();// 评分score = negativeMaximumWithNoCut(analysisBean, oppositeCurPart, -best);// 退回上一步analysisBean.backStep(item.from, to, eatenPiece, invScr);}// 这里添加进所有的分数bestPlace.add(new DoubleBean<>(score, item));if (score > best) { // 找到一个更好的分，就把以前存的位子全部清除best = score;}}/* 排序后返回 */// 这样排序是正确的, 可以有效消减数量bestPlace.sort((o1, o2) -> o2.getO1() - o1.getO1());stepBeanList.clear();bestPlace.forEach(dou -> stepBeanList.add(dou.getO2()));ListPool.localPool().addListToDoubleBeanListPool(bestPlace);}/*** 负极大值搜索算法(不带剪枝算法)** @param analysisBean 局势分析对象* @param curPart 当前走棋方* @return 负极大值搜索算法计算分值*/private static int negativeMaximumWithNoCut(AnalysisBean analysisBean, Part curPart, int alphaBeta) {// 1. 初始化各个变量final Piece[][] pieces = analysisBean.pieces;int best = MIN;// 2. 生成待选的列表，就是可以下子的列表MyList<StepBean> stepBeanList = geneNestStepPlaces(analysisBean, curPart, 1);final Object[] objects = stepBeanList.eleTemplateDate();for (int i = 0, len = stepBeanList.size(); i < len; i++) {final StepBean item = (StepBean) objects[i];Place from = item.from;Place to = item.to;// 备份Piece eatenPiece = pieces[to.x][to.y];int score;// 判断是否胜利if (eatenPiece != null && eatenPiece.role == Role.BOSS) {score = MAX;} else {// 走棋final int invScr = analysisBean.goForward(from, to, eatenPiece);DebugInfo.incrementAlphaBetaOrderTime();score = analysisBean.getCurPartEvaluateScore(curPart);// 退回上一步analysisBean.backStep(from, to, eatenPiece, invScr);}if (score > best) { // 找到一个更好的分，就更新分数best = score;}if (score > alphaBeta) { // alpha剪枝break;}}ListPool.localPool().addListToStepBeanListPool(stepBeanList);return -best;}/*** 奇数层是电脑(max层)thisSide, 偶数层是human(min层)otherSide** @param srcPieces 棋盘* @param curPart 当前走棋方* @param deep 搜索深度* @param forbidStep 禁止的步骤(长捉或长拦)* @return 下一步的位置*/public static Set<StepBean> getEvaluatedPlace(final Piece[][] srcPieces, final Part curPart, final int deep, final StepBean forbidStep) {// 1. 初始化各个变量final AnalysisBean analysisBean = new AnalysisBean(srcPieces);// 2. 获取可以下子的空位列表MyList<StepBean> stepBeanList = geneNestStepPlaces(analysisBean, curPart, deep);// 3. 移除不该下的子stepBeanList.remove(forbidStep);// 进入循环之前计算好循环内使用常量Set<StepBean> bestPlace = new HashSet<>();int best = MIN;// 对方棋手final Part oppositeCurPart = Part.getOpposite(curPart);// 下一深度final int nextDeep = deep - 1;log.debug("size : {}, content: {}", stepBeanList.size(), stepBeanList);final Object[] objects = stepBeanList.eleTemplateDate();for (int i = 0, len = stepBeanList.size(); i < len; i++) {StepBean item = (StepBean) objects[i];final Place to = item.to;// 备份final Piece eatenPiece = srcPieces[to.x][to.y];int score;// 判断是否胜利if (eatenPiece != null && eatenPiece.role == Role.BOSS) {// 步数越少, 分值越大score = MAX + deep;} else {// 走棋final int invScr = analysisBean.goForward(item.from, to, eatenPiece);// 评分if (deep <= 1) {score = analysisBean.getCurPartEvaluateScore(curPart);} else {score = negativeMaximum(analysisBean, oppositeCurPart, nextDeep, -best);}// 退回上一步analysisBean.backStep(item.from, to, eatenPiece, invScr);}if (score == best) { // 找到相同的分数, 就添加这一步bestPlace.add(item);}if (score > best) { // 找到一个更好的分，就把以前存的位子全部清除best = score;bestPlace.clear();bestPlace.add(item);}}ListPool.end();ListPool.localPool().addListToStepBeanListPool(stepBeanList);return bestPlace;}/*** 奇数层是电脑(max层)thisSide, 偶数层是human(min层)otherSide** @param srcPieces 棋盘* @param curPart 当前走棋方* @param deep 搜索深度* @param forbidStep 禁止的步骤(长捉或长拦)* @return 下一步的位置*/public static Set<StepBean> getEvaluatedPlaceWithParallel(final Piece[][] srcPieces, final Part curPart, final int deep, final StepBean forbidStep) {// 1. 初始化各个变量final AnalysisBean srcAnalysisBean = new AnalysisBean(srcPieces);// 2. 获取可以下子的空位列表MyList<StepBean> stepBeanList = geneNestStepPlaces(srcAnalysisBean, curPart, deep);// 3. 移除不该下的子stepBeanList.remove(forbidStep);// 进入循环之前计算好循环内使用常量final Set<StepBean> bestPlace = new HashSet<>();final AtomicInteger best = new AtomicInteger(MIN);// 对方棋手final Part oppositeCurPart = Part.getOpposite(curPart);// 下一深度final int nextDeep = deep - 1;log.debug("size : {}, content: {}", stepBeanList.size(), stepBeanList);Arrays.stream(stepBeanList.toArray()).parallel().filter(Objects::nonNull).map(StepBean.class::cast).forEach(item -> {log.debug("并行流 ==> Thread : {}", Thread.currentThread().getId());final Piece[][] pieces = ArrayUtils.deepClone(srcPieces);final AnalysisBean analysisBean = new AnalysisBean(pieces);final Place to = item.to;// 备份final Piece eatenPiece = pieces[to.x][to.y];int score;// 判断是否胜利if (eatenPiece != null && eatenPiece.role == Role.BOSS) {// 步数越少, 分值越大score = MAX + deep;} else {// 走棋final int invScr = analysisBean.goForward(item.from, to, eatenPiece);// 评分if (deep <= 1) {score = analysisBean.getCurPartEvaluateScore(curPart);} else {score = negativeMaximum(analysisBean, oppositeCurPart, nextDeep, -best.get());}// 退回上一步analysisBean.backStep(item.from, to, eatenPiece, invScr);}if (score == best.get()) { // 找到相同的分数, 就添加这一步synchronized (bestPlace) {bestPlace.add(item);}}if (score > best.get()) { // 找到一个更好的分，就把以前存的位子全部清除best.set(score);synchronized (bestPlace) {bestPlace.clear();bestPlace.add(item);}}ListPool.end();});ListPool.localPool().addListToStepBeanListPool(stepBeanList);ListPool.end();return bestPlace;}/*** 负极大值搜索算法** @param analysisBean 局势分析对象* @param curPart 当前走棋方* @param deep 搜索深度* @param alphaBeta alphaBeta 剪枝分值* @return 负极大值搜索算法计算分值*/private static int negativeMaximum(AnalysisBean analysisBean, Part curPart, int deep, int alphaBeta) {// 1. 初始化各个变量final Piece[][] pieces = analysisBean.pieces;int best = MIN;// 对方棋手final Part oppositeCurPart = Part.getOpposite(curPart);// 下一深度final int nextDeep = deep - 1;// 2. 生成待选的列表，就是可以下子的列表final MyList<StepBean> stepBeanList = geneNestStepPlaces(analysisBean, curPart, deep);final Object[] objects = stepBeanList.eleTemplateDate();for (int i = 0, len = stepBeanList.size(); i < len; i++) {final StepBean item = (StepBean) objects[i];Place from = item.from;Place to = item.to;// 备份Piece eatenPiece = pieces[to.x][to.y];int score;// 判断是否胜利if (eatenPiece != null && eatenPiece.role == Role.BOSS) {// 步数越少, 分值越大score = MAX + deep;} else {// 走棋final int invScr = analysisBean.goForward(from, to, eatenPiece);// 评估if (deep <= 1) {score = analysisBean.getCurPartEvaluateScore(curPart);} else {score = negativeMaximum(analysisBean, oppositeCurPart, nextDeep, -best);}// 退回上一步analysisBean.backStep(from, to, eatenPiece, invScr);}if (score > best) { // 找到一个更好的分，就更新分数best = score;}if (score > alphaBeta) { // alpha剪枝break;}}ListPool.localPool().addListToStepBeanListPool(stepBeanList);return -best;}}