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steffen-illium 2021-06-02 09:17:51 +02:00
parent ff9846eb54
commit dfca68cbeb
5 changed files with 27 additions and 24 deletions
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31
environments/factory/base_factory.py
View File

@ -113,15 +113,19 @@ class BaseFactory(gym.Env):
def movement_actions(self):
return self._actions.movement_actions
def __init__(self, level='simple', n_agents=1, max_steps=int(5e2), pomdp_radius: Union[None, int] = None, **kwargs):
def __init__(self, level='simple', n_agents=1, max_steps=int(5e2), pomdp_radius: Union[None, int] = None,
allow_square_movement=True, allow_diagonal_movement=True, allow_no_op=True, **kwargs):
self.allow_no_op = allow_no_op
self.allow_diagonal_movement = allow_diagonal_movement
self.allow_square_movement = allow_square_movement
self.n_agents = n_agents
self.max_steps = max_steps
self.pomdp_radius = pomdp_radius
self.done_at_collision = False
_actions = Actions(allow_square_movement=kwargs.get('allow_square_movement', True),
allow_diagonal_movement=kwargs.get('allow_diagonal_movement', True),
allow_no_op=kwargs.get('allow_no_op', True))
_actions = Actions(allow_square_movement=self.allow_square_movement,
allow_diagonal_movement=self.allow_diagonal_movement,
allow_no_op=allow_no_op)
self._actions = _actions + self.additional_actions
self._level = h.one_hot_level(
@ -165,12 +169,16 @@ class BaseFactory(gym.Env):
pos = self._agent_states[0].pos
# pos = [agent_state.pos for agent_state in self.agent_states]
# obs = [] ... list comprehension... pos per agent
npad = [(0, 0)] + [(self.pomdp_radius, self.pomdp_radius)] * (self._state.ndim - 1)
x_roll = self.pomdp_radius-pos[0]
y_roll = self.pomdp_radius-pos[1]
padded_state = np.pad(self._state, pad_width=npad, mode='constant', constant_values=0)
padded_state = np.roll(np.roll(padded_state, x_roll, axis=1), y_roll, axis=2)
obs = padded_state[:, :self.pomdp_radius * 2 + 1, :self.pomdp_radius * 2 + 1]
x0, x1 = max(0, pos[0] - self.pomdp_radius), pos[0] + self.pomdp_radius + 1
y0, y1 = max(0, pos[1] - self.pomdp_radius), pos[1] + self.pomdp_radius + 1
obs = self._state[:, x0:x1, y0:y1]
if obs.shape[1] != self.pomdp_radius ** 2 + 1 or obs.shape[2] != self.pomdp_radius ** 2 + 1:
obs_padded = np.full((obs.shape[0], self.pomdp_radius ** 2 + 1, self.pomdp_radius ** 2 + 1), 1)
a_pos = np.argwhere(obs[h.AGENT_START_IDX] == h.IS_OCCUPIED_CELL)[0]
obs_padded[:,
abs(a_pos[0]-self.pomdp_radius):abs(a_pos[0]-self.pomdp_radius)+obs.shape[1],
abs(a_pos[1]-self.pomdp_radius):abs(a_pos[1]-self.pomdp_radius)+obs.shape[2]] = obs
obs = obs_padded
else:
obs = self._state
return obs
@ -211,8 +219,7 @@ class BaseFactory(gym.Env):
info.update(step_reward=reward, step=self.steps)
obs = self._return_state()
return obs, reward, done, info
return None, reward, done, info
def _is_moving_action(self, action):
return action in self._actions.movement_actions

6
environments/factory/simple_factory.py
View File

@ -150,7 +150,7 @@ class SimpleFactory(BaseFactory):
self.print(f'Agent {agent_state.i} did just clean up some dirt at {agent_state.pos}.')
info_dict.update(dirt_cleaned=1)
else:
reward -= 0.0
reward -= 0.01
self.print(f'Agent {agent_state.i} just tried to clean up some dirt '
f'at {agent_state.pos}, but was unsucsessfull.')
info_dict.update(failed_cleanup_attempt=1)
@ -162,14 +162,14 @@ class SimpleFactory(BaseFactory):
else:
# info_dict.update(collision=1)
# self.print('collision')
reward -= 0.00
reward -= 0.01
else:
info_dict.update(no_op=1)
reward -= 0.00
for entity in list_of_collisions:
info_dict.update({f'agent_{agent_state.i}_vs_{self._state_slices.by_name(entity)}': 1})
info_dict.update({f'agent_{agent_state.i}_vs_{entity}': 1})
info_dict.update(dirt_amount=current_dirt_amount)
info_dict.update(dirty_tile_count=dirty_tiles)

2
environments/logging/plotting.py
View File

@ -1,8 +1,6 @@
import seaborn as sns
from matplotlib import pyplot as plt
PALETTE = 10 * (
"#377eb8",
"#4daf4a",

6
main.py
View File

@ -12,7 +12,6 @@ from environments.factory.simple_factory import DirtProperties, SimpleFactory
from environments.helpers import IGNORED_DF_COLUMNS
from environments.logging.monitor import MonitorCallback
from environments.logging.plotting import prepare_plot
from environments.logging.training import TraningMonitor
warnings.filterwarnings('ignore', category=FutureWarning)
warnings.filterwarnings('ignore', category=UserWarning)
@ -55,7 +54,7 @@ if __name__ == '__main__':
for seed in range(5):
env = SimpleFactory(n_agents=1, dirt_properties=dirt_props, pomdp_radius=2, max_steps=400,
allow_diagonal_movement=False, allow_no_op=False, verbose=True)
allow_diagonal_movement=False, allow_no_op=False, verbose=False)
model = modeL_type("MlpPolicy", env, verbose=1, seed=seed, device='cpu')
@ -65,8 +64,7 @@ if __name__ == '__main__':
out_path /= identifier
callbacks = CallbackList(
[TraningMonitor(out_path / f'train_logging_{identifier}.csv'),
MonitorCallback(env, filepath=out_path / f'monitor_{identifier}.pick', plotting=False)]
[MonitorCallback(env, filepath=out_path / f'monitor_{identifier}.pick', plotting=False)]
)
model.learn(total_timesteps=int(2e5), callback=callbacks)

6
reload_agent.py
View File

@ -14,13 +14,13 @@ warnings.filterwarnings('ignore', category=UserWarning)
if __name__ == '__main__':
out_path = Path(r'C:\Users\steff\projects\f_iks\debug_out\A2C_1622557712')
out_path = Path(r'C:\Users\steff\projects\f_iks\debug_out\A2C_1622558379')
with (out_path / f'env_{out_path.name}.pick').open('rb') as f:
env_kwargs = pickle.load(f)
env = SimpleFactory(**env_kwargs)
env = SimpleFactory(allow_no_op=False, allow_diagonal_movement=False, allow_square_movement=True, **env_kwargs)
# Edit THIS:
model_path = out_path
model_path = out_path / '1_A2C_1622558379'
model_files = list(natsorted(out_path.rglob('*.zip')))
this_model = model_files[0]