def benchmark(game, episode_num, grid_size):
winTotal = 0.0
drawTotal = 0.0
for i in range(episode_num):
if (i % 100 == 0): print('hundered episodes completed:', i)
game = dotsnboxes(grid_size)
firstTurn = random.randint(0, 1)
# print(firstTurn)
if firstTurn == 1:
aiCharacter = 2
userLetter = 1
else:
aiCharacter = 1
userLetter = 2
aiAgent = deepai(game, grid_size, 1, 0.1, 0.95, 1.0, 0.01, 100)
aiAgent.loadFromCsv()
turn = firstTurn
gameOn = 1
while gameOn == 1:
## 1 means AI turn
if game.player == aiCharacter:
aiAgent.getMoveVsHuman()
if game.isBoardFull():
# game.drawBoard()
gameOn = 0
# user turn
else:
# game.drawBoard()
# print(game.availMove())
# print('Its player ' + str(game.player) + ' turn')
i, j = random.choice(
game.availMove()
) #raw_input('Enter the moves from the above listed moves: ').split()
# print('User entered move')
game.makeMove([], int(i), int(j))
if game.isBoardFull():
# game.drawBoard()
gameOn = 0
# print('winner is ' + str(game.winner()))
if game.winner() == aiCharacter:
winTotal = winTotal + 1
elif game.winner() == 0:
drawTotal = drawTotal + 1
else:
continue
print('Total Episode :', episode_num)
print('Win percentage is: ', winTotal / episode_num)
print('Draw percentage is: ', drawTotal / episode_num)
def play(grid_size):
game = dotsnboxes(grid_size)
firstTurn = random.randint(0, 1)
print(firstTurn)
if firstTurn == 1:
aiCharacter = 2
userLetter = 1
else:
aiCharacter = 1
userLetter = 2
aiAgent = deepai(game, grid_size, 1, 0.1, 0.95, 1.0, 0.01, 100)
aiAgent.loadFromCsv()
turn = firstTurn
gameOn = 1
while gameOn == 1:
## 1 means AI turn
if game.player == aiCharacter:
aiAgent.getMoveVsHuman()
if game.isBoardFull():
game.drawBoard()
gameOn = 0
# user turn
else:
game.drawBoard()
print(game.availMove())
print('Its player ' + str(game.player) + ' turn')
i, j = raw_input(
'Enter the moves from the above listed moves: ').split()
# print('User entered move')
game.makeMove([], int(i), int(j))
if game.isBoardFull():
game.drawBoard()
gameOn = 0
print('winner is ' + str(game.winner()))
def trainAI(grid_size, episode_num):
# ticGame = tictactoe('X', ' '*9)
aiAgent = deepai(dotsnboxes, grid_size, 1, 0.1, 0.95, 1.0, 0.01,
episode_num)
aiAgent.trainFromEpisode()
aiAgent.write2csv()