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Rework of Observations and Entity Differentiation, lazy obs build by notification

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This commit is contained in:
Steffen Illium
2021-12-22 10:48:36 +01:00
parent 7f7a3d9a3b
commit b43f595207
14 changed files with 961 additions and 487 deletions
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97
environments/factory/factory_dirt.py
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@ -6,11 +6,11 @@ import random
import numpy as np
from algorithms.TSP_dirt_agent import TSPDirtAgent
from environments.helpers import Constants as c
from environments.helpers import Constants as c, Constants
from environments import helpers as h
from environments.factory.base.base_factory import BaseFactory
from environments.factory.base.objects import Agent, Action, Entity, Tile
from environments.factory.base.registers import Entities, MovingEntityObjectRegister
from environments.factory.base.registers import Entities, MovingEntityObjectRegister, EntityRegister
from environments.factory.base.renderer import RenderEntity
from environments.utility_classes import ObservationProperties
@ -42,6 +42,7 @@ class Dirt(Entity):
def amount(self):
return self._amount
@property
def encoding(self):
# Edit this if you want items to be drawn in the ops differntly
return self._amount
@ -52,6 +53,7 @@ class Dirt(Entity):
def set_new_amount(self, amount):
self._amount = amount
self._register.notify_change_to_value(self)
def summarize_state(self, **kwargs):
state_dict = super().summarize_state(**kwargs)
@ -59,18 +61,7 @@ class Dirt(Entity):
return state_dict
class DirtRegister(MovingEntityObjectRegister):
def as_array(self):
if self._array is not None:
self._array[:] = c.FREE_CELL.value
for dirt in list(self.values()):
if dirt.amount == 0:
self.delete_entity(dirt)
self._array[0, dirt.x, dirt.y] = dirt.amount
else:
self._array = np.zeros((1, *self._level_shape))
return self._array
class DirtRegister(EntityRegister):
_accepted_objects = Dirt
@ -93,7 +84,7 @@ class DirtRegister(MovingEntityObjectRegister):
if not self.amount > self.dirt_properties.max_global_amount:
dirt = self.by_pos(tile.pos)
if dirt is None:
dirt = Dirt(tile, amount=self.dirt_properties.max_spawn_amount)
dirt = Dirt(tile, self, amount=self.dirt_properties.max_spawn_amount)
self.register_item(dirt)
else:
new_value = dirt.amount + self.dirt_properties.max_spawn_amount
@ -155,7 +146,7 @@ class DirtFactory(BaseFactory):
new_dirt_amount = dirt.amount - self.dirt_prop.clean_amount
if new_dirt_amount <= 0:
self[c.DIRT].delete_entity(dirt)
self[c.DIRT].delete_env_object(dirt)
else:
dirt.set_new_amount(max(new_dirt_amount, c.FREE_CELL.value))
return c.VALID
@ -224,6 +215,11 @@ class DirtFactory(BaseFactory):
done = self.dirt_prop.done_when_clean and (len(self[c.DIRT]) == 0)
return super_done or done
def _additional_observations(self) -> Dict[Constants, np.typing.ArrayLike]:
additional_observations = super()._additional_observations()
additional_observations.update({c.DIRT: self[c.DIRT].as_array()})
return additional_observations
def calculate_additional_reward(self, agent: Agent) -> (int, dict):
reward, info_dict = super().calculate_additional_reward(agent)
dirt = [dirt.amount for dirt in self[c.DIRT]]
@ -278,41 +274,52 @@ if __name__ == '__main__':
)
obs_props = ObservationProperties(render_agents=ARO.COMBINED, omit_agent_self=True,
pomdp_r=2, additional_agent_placeholder=None)
pomdp_r=2, additional_agent_placeholder=None, cast_shadows=True)
move_props = {'allow_square_movement': True,
'allow_diagonal_movement': False,
'allow_no_op': False}
global_timings = []
for i in range(20):
factory = DirtFactory(n_agents=1, done_at_collision=False,
level_name='rooms', max_steps=400,
doors_have_area=False,
obs_prop=obs_props, parse_doors=True,
record_episodes=True, verbose=True,
mv_prop=move_props, dirt_prop=dirt_props,
inject_agents=[TSPDirtAgent]
)
factory = DirtFactory(n_agents=2, done_at_collision=False,
level_name='rooms', max_steps=1000,
doors_have_area=False,
obs_prop=obs_props, parse_doors=True,
record_episodes=True, verbose=True,
mv_prop=move_props, dirt_prop=dirt_props,
# inject_agents=[TSPDirtAgent],
)
# noinspection DuplicatedCode
n_actions = factory.action_space.n - 1
_ = factory.observation_space
for epoch in range(10):
random_actions = [[random.randint(0, n_actions) for _
in range(factory.n_agents)] for _
in range(factory.max_steps+1)]
env_state = factory.reset()
if render:
factory.render()
tsp_agent = factory.get_injected_agents()[0]
r = 0
for agent_i_action in random_actions:
env_state, step_r, done_bool, info_obj = factory.step(tsp_agent.predict())
r += step_r
# noinspection DuplicatedCode
n_actions = factory.action_space.n - 1
_ = factory.observation_space
obs_space = factory.observation_space
obs_space_named = factory.named_observation_space
times = []
import time
for epoch in range(10):
start_time = time.time()
random_actions = [[random.randint(0, n_actions) for _
in range(factory.n_agents)] for _
in range(factory.max_steps+1)]
env_state = factory.reset()
if render:
factory.render()
if done_bool:
break
print(f'Factory run {epoch} done, reward is:\n {r}')
# tsp_agent = factory.get_injected_agents()[0]
r = 0
for agent_i_action in random_actions:
env_state, step_r, done_bool, info_obj = factory.step(agent_i_action)
r += step_r
if render:
factory.render()
if done_bool:
break
times.append(time.time() - start_time)
# print(f'Factory run {epoch} done, reward is:\n {r}')
print('Time Taken: ', sum(times) / 10)
global_timings.append(sum(times) / 10)
print('Time Taken: ', sum(global_timings[10:]) / 10)
pass