1.阿尔法元之五子棋源码解读(AlphaZero-Gomoku)
2.java ç¨åºè®¾è®¡
3.围棋AI及GUI的围棋使用简介
阿尔法元之五子棋源码解读(AlphaZero-Gomoku)
阿尔法元在五子棋领域的源码解析揭示了强化学习在简单游戏中的深度应用。相较于围棋,保存五子棋虽简单,源码但其源码分析同样能让我们深入理解强化学习的围棋原理。AlphaZero,保存最初凭借阿尔法狗的源码atr指标源码变色深度学习技术,后在没有人类干预的围棋情况下,通过三天自学围棋并超越前辈,保存展现了人工智能的源码新里程碑。
本文着重探讨AlphaZero在五子棋上的围棋具体应用,源码可在GitHub上获取,保存路径公开。源码理解该项目的围棋前提是对强化学习有一定基础,如马尔可夫决策过程和蒙特卡洛方法。保存项目主要包含策略价值网络、源码蒙特卡洛树搜索算法和训练脚本,它们共同构建了强化学习与深度学习的禁雷红包源码交互过程。
项目的架构包括游戏处理、MCTS算法实现、策略价值网络训练以及人机对战脚本。Game.py定义了棋盘和游戏逻辑,mcts_alphaZero.py与mcts_pure.py则是MCTS玩家的实现,分别对应AlphaZero和纯MCTS版本。policy_value_net.py负责网络模型,根据不同框架实现,手机充值源码下载如Tensorflow或Pytorch。train.py则实现了AlphaZero的训练流程,通过模拟对弈和数据增强来优化网络。
运行项目,你可以通过human_play.py与预训练的AI对战,感受强化学习的力量。源码剖析中,human_play.py脚本的木头数卡源码核心是创建棋盘、玩家,并通过循环进行人机对弈,直到游戏结束。
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package com.test;
import java.awt.*;
import java.util.*;
import java.awt.geom.*;
import java.awt.event.*;
import javax.swing.*;
public class MyFiveChess {
public static void main(String[] args) {
JFrame f = new JFrame();
f.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
Dimension screenSize = Toolkit.getDefaultToolkit().getScreenSize();
int screenWidth = screenSize.width;
int screenHeight = screenSize.height;
f.setSize(screenWidth / 2, screenHeight / 2);
f.setLocation(screenWidth / 4, screenHeight / 4);
f.setTitle("FiveChess");
MyPanel panel = new MyPanel();
f.add(panel);
f.setVisible(true);
}
}
class MyPanel extends JPanel {
private static final int SIDELENGTH = ;
private ArrayList<Ellipse2D> squares = new ArrayList<Ellipse2D>();;
private Ellipse2D current = null;
JButton jb = new JButton("éæ°å¼å§");
JButton jb2 = new JButton("åæ¢å æ");
boolean isBlack;
boolean first = true;
boolean isOver;
int l = ;
int n = ;
int bx = ;
int by = ;
int[][] position = new int[n + 1][n + 1];
public MyPanel(){
jb.addActionListener(new MyActionHandler());
jb2.addActionListener(new MyActionHandler());
addMouseListener(new MouseHandler());
addMouseMotionListener(new MouseMotionHandler());
add(jb);
add(jb2);
}
public void initMyPenal(){
squares = new ArrayList<Ellipse2D>();
current = null;
isBlack = first;
isOver = false;
position = new int[n + 1][n + 1];
for(int i = 0; i <= n; i++)
for(int j = 0; j <= n; j++)
position[i][j] = 0;
repaint();
}
public void paint(Graphics g) {
super.paint(g);
jb.setLocation(,);
jb2.setLocation(,);
g.setColor(Color.RED);
g.setFont(new Font(null, Font.BOLD, ));
g.drawString((first ? "é»" : "ç½")+"æ¹ä¸å", , );
g.setColor(new Color(, , ));
g.fillRect(bx - l, by - l, l * (n + 2), l * (n + 2));
g.setColor(Color.BLACK);
for (int i = 0; i <= n; i++){
g.drawLine(bx, by + i * l, bx + l * n, by + i * l);
g.drawLine(bx + i * l, by, bx + i * l, by + l * n);
}
Graphics2D g2 = (Graphics2D)g;
isBlack = first;
for(Ellipse2D r : squares){
g2.setColor(isBlack ? Color.BLACK : Color.WHITE);
g2.fill(r);
isBlack = !isBlack;
}
if(isOver) {
g.setColor(Color.RED);
g.setFont(new Font("TimesRoman", Font.BOLD, ));
g.drawString((isBlack ? "ç½" : "é»") + "æ¹è·è", , );
}
}
public Ellipse2D find(Point2D p){
for(Ellipse2D r : squares)
if(r.contains(p))
return r;
return null;
}
public void add(Point2D p) {
if(p.getX() > bx - l / 2 && p.getX() < bx + l * n + l / 2 &&
p.getY() > by - l / 2 && p.getY() < by + l * n + l / 2){
for (int i = 0; i <= n; i++) {
for (int j = 0; j <= n; j++) {
if(position[i][j] == 1 || position[i][j] == -1) continue;
current = new Ellipse2D.Double(bx + j * l - l / 2,
by + i * l - l / 2, l, l);
if (current.contains(p)) {
position[i][j] = isBlack ? 1 : -1;
isOver = isWin(position, isBlack, i , j) ? true : false;
current.setFrame(bx + j * l - l / 2 + 1,
by + i * l - l / 2 + 1, l - 2, l - 2);
squares.add(current);
repaint();
return;
}
}
}
}
}
private class MouseHandler extends MouseAdapter{
public void mousePressed(MouseEvent event){
if(isOver) return;
current = find(event.getPoint());
if(current == null)
add(event.getPoint());
}
}
private class MyActionHandler implements ActionListener{
public void actionPerformed(ActionEvent e) {
String cmd=e.getActionCommand();
if("éæ°å¼å§".equals(cmd)){
initMyPenal();
}else if("åæ¢å æ".equals(cmd)){
initMyPenal();
first=!first;
}
}
}
private class MouseMotionHandler implements MouseMotionListener{
public void mouseMoved(MouseEvent event){
Rectangle r = new Rectangle(bx - l, by - l, l * (n + 2), l * (n + 2));
if(r.contains(event.getPoint())){
setCursor(Cursor.getPredefinedCursor(Cursor.CROSSHAIR_CURSOR));
}else setCursor(Cursor.getDefaultCursor());
}
public void mouseDragged(MouseEvent event){ }
}
public boolean isWin(int[][] state, boolean isBlack, int x, int y) { //å个æ¹åä¸æ¯å¦æäºåè¿ç
return isCzWin(state, isBlack, x, y)
|| isSpWin(state, isBlack, x, y)
|| isYxWin(state, isBlack, x, y)
|| isZxWin(state, isBlack, x, y);
}
public boolean isCzWin(int[][] state, boolean isBlack, int x, int y) { //å¤æåç´æ¹åæ¯å¦æäºåè¿ç
int n = 0;
int a = (x >= 4 ? x - 4 : 0);
int b = (x <= state.length - 5 ? x + 4 : state.length - 1);
for (int i = a; i <= b; i++)
if (state[i][y] == (isBlack ? 1: -1)) {
if (++n == 5) return true;
} else n = 0;
return false;
}
public boolean isSpWin(int[][] state, boolean isBlack, int x, int y) { //å¤ææ°´å¹³æ¹åæ¯å¦æäºåè¿ç
int n = 0;
int a = (y >= 4 ? y - 4 : 0);
int b = (y <= state[0].length - 5 ? y + 4 : state[0].length - 1);
for (int i = a; i <= b; i++)
if (state[x][i] == (isBlack ? 1: -1)) {
if (++n == 5) return true;
} else n = 0;
return false;
}
public boolean isZxWin(int[][] state, boolean isBlack, int x, int y) { //å¤æå·¦ææ¹åæ¯å¦æäºåè¿ç
int n = 1, a = x, b = y;
for (int i = 1; i <= 4 && a > 0 && b > 0; i++)
if (state[a - 1][b - 1] == (isBlack ? 1: -1)) {
n++; a--; b--;
} else break;
for (int i = 1; i <= 4 && x < state.length - 1 && y < state[0].length - 1; i++)
if (state[x + 1][y + 1] == (isBlack ? 1: -1)) {
n++; x++; y++;
} else break;
if (n >= 5) return true;
return false;
}
public boolean isYxWin(int[][] state, boolean isBlack, int x, int y) { //å¤æå³ææ¹åæ¯å¦æäºåè¿ç
int n = 1, a = x, b = y;
for (int i = 1; i <= 4 && a > 0 && b < state[0].length - 1; i++)
if (state[a - 1][b + 1] == (isBlack ? 1: -1)) {
n++; a--; b++;
} else break;
for (int i = 1; i <= 4 && x < state.length - 1 && y > 0; i++)
if (state[x + 1][y - 1] == (isBlack ? 1: -1)) {
n++; x++; y--;
} else break;
if (n >= 5) return true;
return false;
}
}
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围棋AI及GUI的使用简介
围棋AI的崛起与进步: KataGo,这款强大的AI在入门级设备上也能游刃有余,通过kata1-bcx2-s-d模型运行,每步仅需3秒。在性能相对较低的快应用源码下载手机处理器上,它甚至能展现出超越笔记本5-倍的计算能力,让“地球人”也有了挑战的可能。 围棋AI的选择与获取: AI世界根据功能和开放程度分为五个等级。A类是商业级别的封闭源码,棋力有限;B、C类则是商业性质的付费选项,部分提供免费试用;D类为开源免费,如KataGo、SAI等,可能需要用户自行编译或调整参数;E类则是一键即用,如KaTrain和q5Go,无需额外配置。 安装与使用开源围棋AI: 对于A类,确保硬件兼容至关重要;B、C类可能需要额外的安装步骤或编程技能;D类则是将GUI与AI完美结合;E类则直接适用于那些寻求便捷的用户。 使用中的注意事项: 开源软件可能涉及兼容性挑战,务必关注电脑性能负载。在移动设备上,LazyBaduk和BadukAI等应用可供选择。使用时,AI不仅是分析工具,它能揭示棋局中的恶手并提供推荐,但切勿盲目依赖,保持理性思考。 围棋GUI的优势与应用: GUI界面通常以简洁的蓝底粗体设计呈现,易于理解和操作。搜索关键词"weiqi"和"AI",在项目主页上寻找装配指导。通过AI的深度学习,你可以提升棋艺,理解推荐策略,而非盲目崇拜。术语解析:AI软件,开源意味着源代码公开,而围棋,也就是我们常说的"weiqi"。如果你对围棋AI有更深入的兴趣,这里推荐一篇深入探讨的文章。