def play_games():
won_games = []
with tf.name_scope('play_game'):
for _ in range(ITTERCOUNT):
#generate new game
game = TicTac(net=True, rand=True)
# Get board state as flat vector
inputs = list(game.boards[0])
inputs.extend(game.boards[1])
res = sess.run(results, feed_dict={x: [inputs]})
while game.winner == False:
game.visual()
game.doturn(netvals=res[0])
game.winner = game.check_win()
if game.history[0] == 'X':
#learn the last two moves
won_games.append(game.history[1:])
#take winning games and build training data
print(len(won_games))
for game in won_games:
for move in game:
inputvals.append(move[0])
targetvals.append(vote_for(move[1]))
print(len(won_games) / float(ITTERCOUNT))
