agent = Agent()
sample = 'waiting'
solver = Solver()
playfield = Playfield()
current_tetromino = agent.start_game()
block_num = 0
game_over = False
while not game_over:
block_num += 1
# decide outcome
chosen_outcome = solver.decide_outcome(playfield, current_tetromino)
# execute outcome
next_shape = agent.execute_outcome_and_sample(chosen_outcome,
interval=0.04,
sleep=0.4)
playfield.execute_outcome(chosen_outcome, current_tetromino)
# decode old sample and get new sample
try:
current_tetromino = Tetromino(next_shape)
except:
game_over = True
print('GAME OVER, {} blocks placed'.format(block_num))
filter(lambda outcome: outcome['cost'] == lowest_cost, outcomes))
# if None was swapped out, ban hold for next turn
self.ban_hold = outcomes[0]['tetromino'] == None
# With multiple lowest cost outcomes, selection is only affected by
# number of keystrokes outcome requires. The lowest outcome in the
# list is more likely to not require swap and not require any
# rotations
return outcomes[0]
if __name__ == "__main__":
solver = Solver()
playfield = Playfield()
game_over = False
shape = random.choice(Tetromino.SHAPES)
tetromino = Tetromino(shape)
tetromino = playfield.hold_tetromino(tetromino)
score = 0
while not game_over:
shape = random.choice(Tetromino.SHAPES)
tetromino = Tetromino(shape)
chosen_outcome = solver.decide_outcome(playfield, tetromino)
playfield.execute_outcome(chosen_outcome, tetromino)
print('score = {}, cost = {}'.format(score, chosen_outcome['cost']))
print(playfield)
score += 1
print('GAME OVER, score = {}'.format(score))
print(chosen_outcome)