AI人机对战黑白棋_黑白棋人机对战

没有界面，在终端显示，这是我改编的一个八年前的老项目，没啥好玩的，学习的话值得推荐。

import os, copy
n = 8 # 板子尺寸（偶数）
board = [['0' for x in range(n)] for y in range(n)]
# 8个方向
dirx = [-1, 0, 1, -1, 1, -1, 0, 1]
diry = [-1, -1, -1, 0, 0, 1, 1, 1]

def InitBoard():
    if n % 2 == 0: # 如果板子是偶数
        z = int((n - 2) / 2)
        board[z][z] = '2'
        board[n - 1 - z][z] = '1'        
        board[z][n - 1 - z] = '1'
        board[n - 1 - z][n - 1 - z] = '2'
        
def PrintBoard():
    m = len(str(n - 1))
    for y in range(n):
        row = ''
        for x in range(n):
            row += board[y][x]
            row += ' ' * m
        print(row + ' ' + str(y))
    print()
    row = ''
    for x in range(n):
        row += str(x).zfill(m) + ' '
    print(row + '\n')

def MakeMove(board, x, y, player): # 采取有效措施
    totctr = 0 # 对手总数
    board[y][x] = player
    for d in range(8): # 8个方向
        ctr = 0
        for i in range(n):
            dx = x + dirx[d] * (i + 1)
            dy = y + diry[d] * (i + 1)
            if dx < 0 or dx > n - 1 or dy < 0 or dy > n - 1:
                ctr = 0; break
            elif board[dy][dx] == player:
                break
            elif board[dy][dx] == '0':
                ctr = 0; break
            else:
                ctr += 1
        for i in range(ctr):
            dx = x + dirx[d] * (i + 1)
            dy = y + diry[d] * (i + 1)
            board[dy][dx] = player
        totctr += ctr
    return (board, totctr)

def ValidMove(board, x, y, player):
    if x < 0 or x > n - 1 or y < 0 or y > n - 1:
        return False
    if board[y][x] != '0':
        return False
    (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
    if totctr == 0:
        return False
    return True

minEvalBoard = -1 # min - 1
maxEvalBoard = n * n + 4 * n + 4 + 1 # max + 1
def EvalBoard(board, player):
    tot = 0
    for y in range(n):
        for x in range(n):
            if board[y][x] == player:
                if (x == 0 or x == n - 1) and (y == 0 or y == n - 1):
                    tot += 4 # corner
                elif (x == 0 or x == n - 1) or (y == 0 or y == n - 1):
                    tot += 2 # side
                else:
                    tot += 1
    return tot

# 如果没有有效的动作，则为真
def IsTerminalNode(board, player):
    for y in range(n):
        for x in range(n):
            if ValidMove(board, x, y, player):
                return False
    return True

def GetSortedNodes(board, player):
    sortedNodes = []
    for y in range(n):
        for x in range(n):
            if ValidMove(board, x, y, player):
                (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                sortedNodes.append((boardTemp, EvalBoard(boardTemp, player)))
    sortedNodes = sorted(sortedNodes, key = lambda node: node[1], reverse = True)
    sortedNodes = [node[0] for node in sortedNodes]
    return sortedNodes

def Minimax(board, player, depth, maximizingPlayer):
    if depth == 0 or IsTerminalNode(board, player):
        return EvalBoard(board, player)
    if maximizingPlayer:
        bestValue = minEvalBoard
        for y in range(n):
            for x in range(n):
                if ValidMove(board, x, y, player):
                    (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                    v = Minimax(boardTemp, player, depth - 1, False)
                    bestValue = max(bestValue, v)
    else: # minimizingPlayer
        bestValue = maxEvalBoard
        for y in range(n):
            for x in range(n):
                if ValidMove(board, x, y, player):
                    (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                    v = Minimax(boardTemp, player, depth - 1, True)
                    bestValue = min(bestValue, v)
    return bestValue

def AlphaBeta(board, player, depth, alpha, beta, maximizingPlayer):
    if depth == 0 or IsTerminalNode(board, player):
        return EvalBoard(board, player)
    if maximizingPlayer:
        v = minEvalBoard
        for y in range(n):
            for x in range(n):
                if ValidMove(board, x, y, player):
                    (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                    v = max(v, AlphaBeta(boardTemp, player, depth - 1, alpha, beta, False))
                    alpha = max(alpha, v)
                    if beta <= alpha:
                        break # beta cut-off
        return v
    else: # 最小化播放器
        v = maxEvalBoard
        for y in range(n):
            for x in range(n):
                if ValidMove(board, x, y, player):
                    (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                    v = min(v, AlphaBeta(boardTemp, player, depth - 1, alpha, beta, True))
                    beta = min(beta, v)
                    if beta <= alpha:
                        break # alpha cut-off
        return v

def AlphaBetaSN(board, player, depth, alpha, beta, maximizingPlayer):
    if depth == 0 or IsTerminalNode(board, player):
        return EvalBoard(board, player)
    sortedNodes = GetSortedNodes(board, player)
    if maximizingPlayer:
        v = minEvalBoard
        for boardTemp in sortedNodes:
            v = max(v, AlphaBetaSN(boardTemp, player, depth - 1, alpha, beta, False))
            alpha = max(alpha, v)
            if beta <= alpha:
                break # beta cut-off
        return v
    else: # minimizingPlayer
        v = maxEvalBoard
        for boardTemp in sortedNodes:
            v = min(v, AlphaBetaSN(boardTemp, player, depth - 1, alpha, beta, True))
            beta = min(beta, v)
            if beta <= alpha:
                break # alpha cut-off
        return v

def Negamax(board, player, depth, color):
    if depth == 0 or IsTerminalNode(board, player):
        return color * EvalBoard(board, player)
    bestValue = minEvalBoard
    for y in range(n):
        for x in range(n):
            if ValidMove(board, x, y, player):
                (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                v = -Negamax(boardTemp, player, depth - 1, -color)
                bestValue = max(bestValue, v)
    return bestValue

def NegamaxAB(board, player, depth, alpha, beta, color):
    if depth == 0 or IsTerminalNode(board, player):
        return color * EvalBoard(board, player)
    bestValue = minEvalBoard
    for y in range(n):
        for x in range(n):
            if ValidMove(board, x, y, player):
                (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                v = -NegamaxAB(boardTemp, player, depth - 1, -beta, -alpha, -color)
                bestValue = max(bestValue, v)
                alpha = max(alpha, v)
                if alpha >= beta:
                    break
    return bestValue

def NegamaxABSN(board, player, depth, alpha, beta, color):
    if depth == 0 or IsTerminalNode(board, player):
        return color * EvalBoard(board, player)
    sortedNodes = GetSortedNodes(board, player)
    bestValue = minEvalBoard
    for boardTemp in sortedNodes:
        v = -NegamaxABSN(boardTemp, player, depth - 1, -beta, -alpha, -color)
        bestValue = max(bestValue, v)
        alpha = max(alpha, v)
        if alpha >= beta:
            break
    return bestValue

def Negascout(board, player, depth, alpha, beta, color):
    if depth == 0 or IsTerminalNode(board, player):
        return color * EvalBoard(board, player)
    firstChild = True
    for y in range(n):
        for x in range(n):
            if ValidMove(board, x, y, player):
                (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                if not firstChild:
                    score = -Negascout(boardTemp, player, depth - 1, -alpha - 1, -alpha, -color)
                    if alpha < score and score < beta:
                        score = -Negascout(boardTemp, player, depth - 1, -beta, -score, -color)
                else:
                    firstChild = False
                    score = -Negascout(boardTemp, player, depth - 1, -beta, -alpha, -color)
                alpha = max(alpha, score)
                if alpha >= beta:
                    break
    return alpha

def NegascoutSN(board, player, depth, alpha, beta, color):
    if depth == 0 or IsTerminalNode(board, player):
        return color * EvalBoard(board, player)
    sortedNodes = GetSortedNodes(board, player)
    firstChild = True
    for boardTemp in sortedNodes:
        if not firstChild:
            score = -NegascoutSN(boardTemp, player, depth - 1, -alpha - 1, -alpha, -color)
            if alpha < score and score < beta:
                score = -NegascoutSN(boardTemp, player, depth - 1, -beta, -score, -color)
        else:
            firstChild = False
            score = -NegascoutSN(boardTemp, player, depth - 1, -beta, -alpha, -color)
        alpha = max(alpha, score)
        if alpha >= beta:
            break
    return alpha

def BestMove(board, player):
    maxPoints = 0
    mx = -1; my = -1
    for y in range(n):
        for x in range(n):
            if ValidMove(board, x, y, player):
                (boardTemp, totctr) = MakeMove(copy.deepcopy(board), x, y, player)
                if opt == 0:
                    points = EvalBoard(boardTemp, player) 
                elif opt == 1:
                    points = Minimax(boardTemp, player, depth, True)
                elif opt == 2:
                    points = AlphaBeta(board, player, depth, minEvalBoard, maxEvalBoard, True)
                elif opt == 3:
                    points = Negamax(boardTemp, player, depth, 1)
                elif opt == 4:
                    points = NegamaxAB(boardTemp, player, depth, minEvalBoard, maxEvalBoard, 1)
                elif opt == 5:
                    points = Negascout(boardTemp, player, depth, minEvalBoard, maxEvalBoard, 1)
                elif opt == 6:
                    points = AlphaBetaSN(board, player, depth, minEvalBoard, maxEvalBoard, True)
                elif opt == 7:
                    points = NegamaxABSN(boardTemp, player, depth, minEvalBoard, maxEvalBoard, 1)
                elif opt == 8:
                    points = NegascoutSN(boardTemp, player, depth, minEvalBoard, maxEvalBoard, 1)
                if points> maxPoints:
                    maxPoints = points
                    mx = x; my = y
    return (mx, my)

print('REVERSI OTHELLO董事会游戏')
print('0: 评估板')
print('1: 极小值')
print('2: 带有Alpha-Beta修剪的Minimax')
print('3: negamax')
print('4: Negamax与Alpha-Beta修剪')
print('5: Negascout（主要变化搜索)')
print('6: 带有排序节点的Alpha-Beta修剪的Minimax')
print('7: N带排序节点的Alpha-Beta修剪的negamax')
print('8: Negascout（主要变异搜索）w排序的节点')
opt = int(input('SelectAIAlgorithm '))
if opt > 0 and opt < 9:
    depth = 4
    depthStr = input('选择搜索深度（默认值：4）: ')
    if depthStr != '': depth = int(depth)
print('\n1: User 2: AI (只需按Enter键即可退出！)')
InitBoard()
while True:
    for p in range(2):
        print()
        PrintBoard()
        player = str(p + 1)
        print('玩家： ' + player)
        if IsTerminalNode(board, player):
            print('玩家无法玩！游戏结束了！')
            print('评分用户： ' + str(EvalBoard(board, '1')))
            print('评分 AI: ' + str(EvalBoard(board, '2')))
            os._exit(0)            
        if player == '1': # user's turn
            while True:
                xy = input('X Y: ')
                if xy == '': os._exit(0)
                (x, y) = xy.split()
                x = int(x); y = int(y)
                if ValidMove(board, x, y, player):
                    (board, totctr) = MakeMove(board, x, y, player)
                    print('# of pieces taken: ' + str(totctr))
                    break
                else:
                    print('无效移动，请重新尝试！')
        else: # AI's turn
            (x, y) = BestMove(board, player)
            if not (x == -1 and y == -1):
                (board, totctr) = MakeMove(board, x, y, player)
                print('AI played (X Y): ' + str(x) + ' ' + str(y))
                print('# of pieces taken: ' + str(totctr))

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320