【转】Python实现智能五子棋
前言
棋需要一步一步下，人生需要一步一步走。千里之行，始于足下，九层之台，起于累土。
用Python五子棋小游戏。
基本环境配置
版本：Python3
相关模块：
本文所做工作如下：
（1） 五子棋界面实现；
（2） 智能判定棋盘走势；
（3） 改进了棋盘扫描方式；
（4） 改良了系统评分表评估方式；
（5） 实现了基于点评分表估值找出最佳落子方式。
实现效果图
emmmm，系统是执白子，小编是执黑子，结果显示，系统赢了，哈哈哈哈....尴尬，不要在在意这些细节，咱们看代码，看代码~~~~
代码实现
from time import sleep
import pygame
from pygame.locals import *
from random import randint
level = 15
grade = 10
MAX = 1008611
def Scan(chesspad, color):
shape = [[[0 for high in range(5)] for col in range(15)] for row in range(15)]
# 扫描每一个点，然后在空白的点每一个方向上做出价值评估！！
for i in range(15):
for j in range(15):
# 如果此处为空 那么就可以开始扫描周边
if chesspad[i][j] == 0:
m = i
n = j
# 如果上方跟当前传入的颜色参数一致，那么加分到0位！
while n - 1 >= 0 and chesspad[m][n - 1] == color:
n -= 1
shape[i][j][0] += grade
if n-1>=0 and chesspad[m][n - 1] == 0:
shape[i][j][0] += 1
if n-1 >= 0 and chesspad[m][n - 1] == -color:
shape[i][j][0] -= 2
m = i
n = j
# 如果下方跟当前传入的颜色参数一致，那么加分到0位！
while (n + 1 < level and chesspad[m][n + 1] == color):
n += 1
shape[i][j][0] += grade
if n + 1 < level and chesspad[m][n + 1] == 0:
shape[i][j][0] += 1
if n + 1 < level and chesspad[m][n + 1] == -color:
shape[i][j][0] -= 2
m = i
n = j
# 如果左边跟当前传入的颜色参数一致，那么加分到1位！
while (m - 1 >= 0 and chesspad[m - 1][n] == color):
m -= 1
shape[i][j][1] += grade
if m - 1 >= 0 and chesspad[m - 1][n] == 0:
shape[i][j][1] += 1
if m - 1 >= 0 and chesspad[m - 1][n] == -color:
shape[i][j][1] -= 2
m = i
n = j
# 如果右边跟当前传入的颜色参数一致，那么加分到1位！
while (m + 1 < level and chesspad[m + 1][n] == color):
m += 1
shape[i][j][1] += grade
if m + 1 < level and chesspad[m + 1][n] == 0:
shape[i][j][1] += 1
if m + 1 < level and chesspad[m + 1][n] == -color:
shape[i][j][1] -= 2
m = i
n = j
# 如果左下方跟当前传入的颜色参数一致，那么加分到2位！
while (m - 1 >= 0 and n + 1 < level and chesspad[m - 1][n + 1] == color):
m -= 1
n += 1
shape[i][j][2] += grade
if m - 1 >= 0 and n + 1 < level and chesspad[m - 1][n + 1] == 0:
shape[i][j][2] += 1
if m - 1 >= 0 and n + 1 < level and chesspad[m - 1][n + 1] == -color:
shape[i][j][2] -= 2
m = i
n = j
# 如果右上方跟当前传入的颜色参数一致，那么加分到2位！
while (m + 1 < level and n - 1 >= 0 and chesspad[m + 1][n - 1] == color):
m += 1
n -= 1
shape[i][j][2] += grade
if m + 1 < level and n - 1 >= 0 and chesspad[m + 1][n - 1] == 0:
shape[i][j][2] += 1
if m + 1 < level and n - 1 >= 0 and chesspad[m + 1][n - 1] == -color:
shape[i][j][2] -= 2
m = i
n = j
# 如果左上方跟当前传入的颜色参数一致，那么加分到3位！
while (m - 1 >= 0 and n - 1 >= 0 and chesspad[m - 1][n - 1] == color):
m -= 1
n -= 1
shape[i][j][3] += grade
if m - 1 >= 0 and n - 1 >= 0 and chesspad[m - 1][n - 1] == 0:
shape[i][j][3] += 1
if m - 1 >= 0 and n - 1 >= 0 and chesspad[m - 1][n - 1] == -color:
shape[i][j][3] -= 2
m = i
n = j
# 如果右下方跟当前传入的颜色参数一致，那么加分到3位！
while m + 1 < level and n + 1 < level and chesspad[m + 1][n + 1] == color:
m += 1
n += 1
shape[i][j][3] += grade
if m + 1 < level and n + 1 < level and chesspad[m + 1][n + 1] == 0:
shape[i][j][3] += 1
if m + 1 < level and n + 1 < level and chesspad[m + 1][n + 1] == -color:
shape[i][j][3] -= 2
return shape
def Sort(shape):
for i in shape:
for j in i:
for x in range(5):
for w in range(3, x - 1, -1):
if j[w - 1] < j[w]:
temp = j[w]
j[w - 1] = j[w]
j[w] = temp
print("This Time Sort Done !")
return shape
def Evaluate(shape):
for i in range(level):
for j in range(level):
if shape[i][j][0] == 4:
return i, j, MAX
shape[i][j][4] = shape[i][j][0]*1000 + shape[i][j][1]*100 + shape[i][j][2]*10 + shape[i][j][3]
max_x = 0
max_y = 0
max = 0
for i in range(15):
for j in range(15):
if max < shape[i][j][4]:
max = shape[i][j][4]
max_x = i
max_y = j
print("the max is "+ str(max) + " at ( "+ str(max_x)+" , "+str(max_y)+" )")
return max_x, max_y, max
class chess(object):
def __init__(self):
self.a = [[0 for high in range(15)] for col in range(15)]
def fall(self, x, y, color):
if (x < 0 or x > level - 1 or y < 0 or y > level - 1):
return
self.a[x][y] = color
if Judge(x, y, color, self.a, 4):
if color < 0:
print("The Winner is White!!")
else:
print("The Winner is Black!!")
def isEmpty(self, m, n):
if self.a[m][n] != 0:
return False
else:
return True
def Judge(x, y, color, CHESSLOCATION, length):
count1, count2, count3, count4 = 0, 0, 0, 0 # 横向判断
i = x - 1
while (i >= 0): if color == CHESSLOCATION[
i][y]: count1 += 1 i -= 1 else: break i = x + 1 while i
< level:
if CHESSLOCATION[i][y] == color:
count1 += 1
i += 1
else:
break # 纵向判断
j = y - 1
while (j >= 0): if CHESSLOCATION[
x][j] == color: count2 += 1 j -= 1 else: break j = y + 1 while j
< level:
if CHESSLOCATION[x][j] == color:
count2 += 1
j += 1
else:
break # 正对角线判断
i, j = x - 1, y - 1
while (i >= 0 and j >= 0): if CHESSLOCATION[
i][j] == color: count3 += 1 i -= 1 j -= 1 else: break i, j = x + 1, y + 1 while (i
< level and j < level):
if CHESSLOCATION[i][j] == color:
count3 += 1
i += 1
j += 1
else:
break # 反对角线判断
i, j = x + 1, y - 1
while (i < level and j >= 0): if CHESSLOCATION[
i][j] == color: count4 += 1 i += 1 j -= 1 else: break i, j = x - 1, y + 1 while (i > 0 and j
< level):
if CHESSLOCATION[i][j] == color:
count4 += 1
i -= 1
j += 1
else:
break
if count1 >= length or count2 >= length or count3 >= length or count4 >= length: return True else: return Falsedef Autoplay(ch, m, n): a1 = [1,-1,1,-1,1,-1,0,0] b1 = [1,-1,-1,1,0,0,1,-1] rand = randint(0,7) while m+a1[
rand]>=0 and m+a1[rand]<level and n+b1[rand]>=0 and n+b1[rand]<level and ch[m+a1[rand]][n+b1[rand]]!=0 :
rand = randint(0,7)
return m + a1[rand], n+b1[rand]
def BetaGo(ch, m, n, color, times):
if times < 2:
return Autoplay(ch, m, n)
else:
shape_P = Scan(ch, -color)
shape_C = Scan(ch,color)
shape_P = Sort(shape_P)
shape_C = Sort(shape_C)
max_x_P, max_y_P, max_P = Evaluate(shape_P)
max_x_C, max_y_C, max_C = Evaluate(shape_C)
if max_P>max_C and max_C<MAX:
return max_x_P,max_y_P
else:
return max_x_C,max_y_C
def satrtGUI(ch):
pygame.init()
bg = 'bg.png'
white_image = 'white.png'
black_image = 'black.png'
screen = pygame.display.set_mode((750, 750), 0, 32)
background = pygame.image.load(bg).convert()
white = pygame.image.load(white_image).convert_alpha()
black = pygame.image.load(black_image).convert_alpha()
white = pygame.transform.smoothscale(white, (int(white.get_width() * 1.5), int(white.get_height() * 1.5)))
black = pygame.transform.smoothscale(black, (int(black.get_width() * 1.5), int(black.get_height() * 1.5)))
screen.blit(background, (0, 0))
font = pygame.font.SysFont("黑体", 40)
pygame.event.set_blocked([1, 4, KEYUP, JOYAXISMOTION, JOYBALLMOTION, JOYBUTTONDOWN, JOYBUTTONUP, JOYHATMOTION])
pygame.event.set_allowed([MOUSEBUTTONDOWN, MOUSEBUTTONUP, 12, KEYDOWN])
dot_list = [(25 + i * 50 - white.get_width() / 2, 25 + j * 50 - white.get_height() / 2) for i in range(level) for
j in range(level)]
color = -1
times = 0
flag = False
while not flag:
for event in pygame.event.get():
if event.type == QUIT:
exit()
elif event.type == MOUSEBUTTONDOWN:
x, y = pygame.mouse.get_pos()
if 25 <= x <= 725 and 25 <= y <= 725 and ((x - 25) % 50 <= level or (x - 25) % 50 >= 0) and ( (y - 25) % 50
<= level or (y - 25) % 50 >= 0): color = -1 * color m = int(round((x - 25) / 50)) n = int(round((y - 25) / 50)) if not ch.isEmpty(m, n): print("Black OverWrite~~") continue ch.fall(m, n, color) screen.blit(black, dot_list[level * m + n]) if Judge(m, n, color, ch.a, 4): screen.blit(font.render('GAME OVER,Black is win!', True, (110, 210, 30)), (80, 650)) break color = -1 * color sleep(0.1) x, y = BetaGo(ch.a, m, n, color, times) times += 1 print("Predict:" + str(x) + " and " + str(y)) ch.fall(x, y, color) screen.blit(white, dot_list[level * x + y]) if Judge(x, y, color, ch.a, 4): screen.blit(font.render('GAME OVER,White is win!', True, (217, 20, 30)), (80, 650)) break pygame.display.update() if flag: sleep(5)now = chess()satrtGUI(now)
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