-
Notifications
You must be signed in to change notification settings - Fork 1
/
ttt_rl.py
296 lines (259 loc) · 9.06 KB
/
ttt_rl.py
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
# Import Libraries
import numpy as np
import pickle
# Define a 3x3 board
BOARD_ROWS = 3
BOARD_COLS = 3
# ### Board States:
# - Two players: p1 and p2
# - p1 uses the symbol 1
# - p2 uses the symbol 2
# - Vacant position is denoted by 0
class State:
def __init__(self, p1, p2):
self.board = np.zeros((BOARD_ROWS, BOARD_COLS))
self.p1 = p1
self.p2 = p2
self.isEnd = False
self.boardHash = None
# p1 plays first
self.playerSymbol = 1
# get unique hash of the current board state
def getHash(self):
self.boardHash = str(self.board.reshape(BOARD_COLS*BOARD_ROWS))
return self.boardHash
def winner(self):
# rows
for i in range(BOARD_ROWS):
if sum(self.board[i, :]) == 3:
self.isEnd = True
return 1
if sum(self.board[i, :]) == -3:
self.isEnd = True
return -1
# columns
for i in range(BOARD_COLS):
if sum(self.board[:, i]) == 3:
self.isEnd = True
return 1
if sum(self.board[:, i]) == -3:
self.isEnd = True
return -1
# diagonals
diag_sum1 = sum([self.board[i, i] for i in range(BOARD_COLS)])
diag_sum2 = sum([self.board[i, BOARD_COLS-i-1] for i in range(BOARD_COLS)])
diag_sum = max(diag_sum1, diag_sum2)
if diag_sum == 3:
self.isEnd = True
return 1
if diag_sum == -3:
self.isEnd = True
return -1
# draw
# no available positions
if len(self.availablePositions()) == 0:
self.isEnd = True
return 0
# not end
self.isEnd = False
return None
def availablePositions(self):
positions = []
for i in range(BOARD_ROWS):
for j in range(BOARD_COLS):
if self.board[i, j] == 0:
positions.append((i, j))
return positions
def updateState(self, position):
self.board[position] = self.playerSymbol
# switch to the other player
self.playerSymbol = -1 if self.playerSymbol == 1 else 1
# giveReward only when game ends
def giveReward(self):
result = self.winner()
# backpropagate reward
if result == 1:
self.p1.feedReward(1)
self.p2.feedReward(0)
elif result == -1:
self.p1.feedReward(0)
self.p2.feedReward(1)
else:
self.p1.feedReward(0.1)
self.p2.feedReward(0.5)
# board reset
def reset(self):
self.board = np.zeros((BOARD_ROWS, BOARD_COLS))
self.boardHash = None
self.isEnd = False
self.playerSymbol = 1
def play(self, rounds=100):
for i in range(rounds):
if i%1000 == 0:
print("Rounds {}".format(i))
while not self.isEnd:
# Player 1
positions = self.availablePositions()
p1_action = self.p1.chooseAction(positions, self.board, self.playerSymbol)
# take action and upate the board state
self.updateState(p1_action)
board_hash = self.getHash()
self.p1.addState(board_hash)
# check board status if it is 'end'
win = self.winner()
if win is not None:
# self.showBoard()
# ended with p1, either win or draw
self.giveReward()
self.p1.reset()
self.p2.reset()
self.reset()
break
else:
# Player 2
positions = self.availablePositions()
p2_action = self.p2.chooseAction(positions, self.board, self.playerSymbol)
self.updateState(p2_action)
board_hash = self.getHash()
self.p2.addState(board_hash)
win = self.winner()
if win is not None:
# self.showBoard()
# ended with p2, either win or draw
self.giveReward()
self.p1.reset()
self.p2.reset()
self.reset()
break
# play with human
def play2(self):
while not self.isEnd:
# Player 1
positions = self.availablePositions()
p1_action = self.p1.chooseAction(positions, self.board, self.playerSymbol)
# take action and upate board state
self.updateState(p1_action)
self.showBoard()
# check board status if it is end
win = self.winner()
if win is not None:
if win == 1:
print(self.p1.name, "wins!")
else:
print("draw!")
self.reset()
break
else:
# Player 2
positions = self.availablePositions()
p2_action = self.p2.chooseAction(positions)
self.updateState(p2_action)
self.showBoard()
win = self.winner()
if win is not None:
if win == -1:
print(self.p2.name, "wins!")
else:
print("draw!")
self.reset()
break
def showBoard(self):
# p1: x p2: o
for i in range(0, BOARD_ROWS):
print('-------------')
out = '| '
for j in range(0, BOARD_COLS):
if self.board[i, j] == 1:
token = 'x'
if self.board[i, j] == -1:
token = 'o'
if self.board[i, j] == 0:
token = ' '
out += token + ' | '
print(out)
print('-------------')
class Player:
def __init__(self, name, exp_rate=0.3):
self.name = name
self.states = [] # record all positions taken
self.lr = 0.2
self.exp_rate = exp_rate
self.decay_gamma = 0.9
self.states_value = {} # state -> value
def getHash(self, board):
boardHash = str(board.reshape(BOARD_COLS*BOARD_ROWS))
return boardHash
def chooseAction(self, positions, current_board, symbol):
if np.random.uniform(0, 1) <= self.exp_rate:
# take random action
idx = np.random.choice(len(positions))
action = positions[idx]
else:
value_max = -999
for p in positions:
next_board = current_board.copy()
next_board[p] = symbol
next_boardHash = self.getHash(next_board)
value = 0 if self.states_value.get(next_boardHash) is None else self.states_value.get(next_boardHash)
# print("value", value)
if value >= value_max:
value_max = value
action = p
return action
# append a hash state
def addState(self, state):
self.states.append(state)
# at the end of game, backpropagate and update states value
def feedReward(self, reward):
for st in reversed(self.states):
if self.states_value.get(st) is None:
self.states_value[st] = 0
self.states_value[st] += self.lr*(self.decay_gamma*reward - self.states_value[st])
reward = self.states_value[st]
def reset(self):
self.states = []
def savePolicy(self):
fw = open('policy_' + str(self.name), 'wb')
pickle.dump(self.states_value, fw)
fw.close()
def loadPolicy(self, file):
fr = open(file,'rb')
self.states_value = pickle.load(fr)
fr.close()
class HumanPlayer:
def __init__(self, name):
self.name = name
def chooseAction(self, positions):
while True:
x = int(input("Your Move--> "))
if x==1:
row, col = 0, 0
elif x==2:
row, col = 0, 1
elif x==3:
row, col = 0, 2
elif x==4:
row, col = 1, 0
elif x==5:
row, col = 1, 1
elif x==6:
row, col = 1, 2
elif x==7:
row, col = 2, 0
elif x==8:
row, col = 2, 1
elif x==9:
row, col = 2, 2
else:
row, col = None, None
action = (row, col)
if action in positions:
return action
# append a hash state
def addState(self, state):
pass
# at the end of game, backpropagate and update states value
def feedReward(self, reward):
pass
def reset(self):
pass