class Player:
def __init__(self,
num_opponents: int,
num_teammates: int,
model_file: str,
epsilon: int = 1,
port: int = 6000):
# Game Interface:
self.game_interface = HFOAttackingPlayer(num_opponents=num_opponents,
num_teammates=num_teammates,
port=port)
self.game_interface.connect_to_server()
# Features Interface:
self.features = PlasticFeatures(num_op=num_opponents,
num_team=num_teammates)
# Actions Interface:
self.actions = Actions(num_team=num_teammates,
features=self.features,
game_interface=self.game_interface)
# Agent instance:
self.epsilon = epsilon
self.dqn = DQN.load(load_file=model_file)
# Metrics:
self.metrics = GameMetrics()
def set_starting_game_conditions(self,
start_pos: tuple = None,
starts_fixed_position: bool = True,
verbose: bool = False):
"""
Set starting game conditions. Move for initial position, for example
"""
if starts_fixed_position:
if not start_pos:
ball_pos: list = list(self.features.get_ball_coord())
starting_corners = get_vertices_around_ball(ball_pos)
start_pos = random.choice(starting_corners)
self.actions.move_to_pos(start_pos)
if verbose:
print(f"[PLAYER: GAME SET UP] Initial pos= {start_pos}")
else:
# Start in current position
if verbose:
print(f"[START GAME] Initial pos= RANDOM")
# Informs the other players that it is ready to start:
self.game_interface.hfo.say(settings.PLAYER_READY_MSG)
def exploit_actions(self, state: np.ndarray, verbose: bool = False) -> int:
q_predict = self.dqn.predict(state)
max_list = np.where(q_predict == q_predict.max())
if len(max_list[0]) > 1:
action = np.random.choice(max_list[0])
else:
action = np.argmax(q_predict)
if verbose:
print("Q values {} -> {}".format(q_predict, int(action)))
return int(action)
def play(self, num_episodes: int, starts_fixed_position: bool = True):
"""
@param num_episodes: number of episodes to train in this iteration
@param starts_fixed_position: bool
@raise ServerDownError
@return: Game Metrics
"""
self.metrics.restart()
for ep in range(num_episodes):
# Check if server still running:
try:
self.game_interface.check_server_is_up()
except ServerDownError:
print("!!SERVER DOWN!! Test {}/{}".format(ep, num_episodes))
metrics_dict = self.metrics.export_to_dict(num_episodes)
return metrics_dict
# Update features:
self.features.update_features(
observation=self.game_interface.get_observation())
# Go to origin position:
self.set_starting_game_conditions(
starts_fixed_position=starts_fixed_position)
# metrics:
touched_ball = False
passed_ball = False
while self.game_interface.in_game():
if self.features.has_ball(): touched_ball = True
# Update environment features:
features_array = self.features.get_features()
# Act:
act = self.exploit_actions(features_array, verbose=False)
status, correct_action, passed_ball_succ = \
self.actions.execute_action(act)
# Metrics:
if passed_ball_succ is True: passed_ball = True
if correct_action:
self.metrics.inc_num_correct_actions()
else:
self.metrics.inc_num_wrong_actions()
# Update auxiliar variables:
self.metrics.inc_num_ep()
if self.game_interface.scored_goal(): self.metrics.inc_num_wins()
if touched_ball: self.metrics.inc_num_games_touched_ball()
if passed_ball: self.metrics.inc_num_games_passed_ball()
# Game Reset
self.game_interface.reset()
metrics_dict = self.metrics.export_to_dict(num_episodes)
return metrics_dict
class Player:
def __init__(self,
num_opponents: int,
num_teammates: int,
model_file: str,
epsilon: int = 1,
port: int = 6000):
# Game Interface:
self.game_interface = HFOAttackingPlayer(num_opponents=num_opponents,
num_teammates=num_teammates,
port=port)
self.game_interface.connect_to_server()
# Features Interface:
self.features = PlasticFeatures(num_op=num_opponents,
num_team=num_teammates)
# Actions Interface:
self.actions = Actions(num_team=num_teammates,
features=self.features,
game_interface=self.game_interface)
# Agent instance:
self.epsilon = epsilon
self.dqn = DQN.load(load_file=model_file)
def exploit_actions(self, state: np.ndarray, verbose: bool = False) -> int:
q_predict = self.dqn.predict(state)
max_list = np.where(q_predict == q_predict.max())
action = np.random.choice(max_list[0]) if len(max_list[0]) > 1 \
else np.argmax(q_predict)
if verbose:
print("Q values {} -> {}".format(q_predict, int(action)))
return int(action)
def explore_actions(self):
random_action = np.random.randint(0, self.actions.num_actions)
return random_action
def act(self, state: np.ndarray, verbose: bool = False):
if np.random.random() < self.epsilon: # Explore
if verbose: print("[ACT] Explored")
return self.explore_actions()
else: # Exploit
if verbose: print("[ACT] Exploit")
return self.exploit_actions(state)
def get_reward(self, game_status: int, correct_action: bool) -> int:
reward = 0
if game_status == GOAL:
reward += 1000
elif game_status in [CAPTURED_BY_DEFENSE, OUT_OF_BOUNDS, OUT_OF_TIME]:
reward -= 1000
else:
if correct_action:
reward += 1
else:
reward -= 5
return reward
def play_episode(self):
# auxiliar structures:
episode_buffer = list()
# metrics:
touched_ball = False
passed_ball = False
num_wrong_actions = 0
num_correct_actions = 0
while self.game_interface.in_game():
touched_ball = True if self.features.has_ball() else False
# Update environment features:
features_array = self.features.get_features()
# Act:
act = self.act(features_array, verbose=False)
status, correct_action, passed_ball_succ = \
self.actions.execute_action(act)
# Store transition:
# (obs, action, reward, new obs, done?)
transition = Transition(obs=features_array,
act=act,
reward=self.get_reward(
status, correct_action),
new_obs=self.features.get_features(),
done=not self.game_interface.in_game(),
correct_action=correct_action)
episode_buffer.append(transition)
# Metrics:
passed_ball = True if passed_ball_succ else False
if correct_action:
num_correct_actions += 1
else:
num_wrong_actions += 1
metrics = EpisodeMetrics(touched_ball=touched_ball,
passed_ball=passed_ball,
num_wrong_actions=num_wrong_actions,
num_correct_actions=num_correct_actions)
return episode_buffer, metrics
def play(self, num_episodes: int, starts_fixed_position: bool = True):
"""
@param num_episodes: number of episodes to train in this iteration
@param starts_fixed_position: bool
@raise ServerDownError
@return: Game Metrics
"""
experience_buffer = LearnBuffer()
game_metrics = GameMetrics()
for ep in range(num_episodes):
# Check if server still running:
try:
self.game_interface.check_server_is_up()
except ServerDownError:
print("!!SERVER DOWN!! Test {}/{}".format(ep, num_episodes))
return experience_buffer, game_metrics.export_to_dict()
# Update features:
self.features.update_features(
observation=self.game_interface.get_observation())
# Play episode:
ep_buffer, ep_metrics = self.play_episode()
# Save episode:
experience_buffer.save_episode(ep_buffer, verbose=True)
# Update auxiliar variables:
game_metrics.add_episode_metrics(
ep_metrics, goal=self.game_interface.scored_goal())
# Game Reset
self.game_interface.reset()
return experience_buffer, game_metrics.export_to_dict()