import time from enum import Enum from typing import List, Union, NamedTuple, Dict import random import numpy as np from algorithms.TSP_dirt_agent import TSPDirtAgent 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, EntityRegister from environments.factory.base.renderer import RenderEntity from environments.utility_classes import ObservationProperties CLEAN_UP_ACTION = h.EnvActions.CLEAN_UP class DirtProperties(NamedTuple): initial_dirt_ratio: float = 0.3 # On INIT, on max how much tiles does the dirt spawn in percent. initial_dirt_spawn_r_var: float = 0.05 # How much does the dirt spawn amount vary? clean_amount: float = 1 # How much does the robot clean with one actions. max_spawn_ratio: float = 0.20 # On max how much tiles does the dirt spawn in percent. max_spawn_amount: float = 0.3 # How much dirt does spawn per tile at max. spawn_frequency: int = 0 # Spawn Frequency in Steps. max_local_amount: int = 2 # Max dirt amount per tile. max_global_amount: int = 20 # Max dirt amount in the whole environment. dirt_smear_amount: float = 0.2 # Agents smear dirt, when not cleaning up in place. agent_can_interact: bool = True # Whether the agents can interact with the dirt in this environment. done_when_clean: bool = True class Dirt(Entity): @property def can_collide(self): return False @property 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 def __init__(self, *args, amount=None, **kwargs): super(Dirt, self).__init__(*args, **kwargs) self._amount = amount 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) state_dict.update(amount=float(self.amount)) return state_dict class DirtRegister(EntityRegister): _accepted_objects = Dirt @property def amount(self): return sum([dirt.amount for dirt in self]) @property def dirt_properties(self): return self._dirt_properties def __init__(self, dirt_properties, *args): super(DirtRegister, self).__init__(*args) self._dirt_properties: DirtProperties = dirt_properties def spawn_dirt(self, then_dirty_tiles) -> c: if isinstance(then_dirty_tiles, Tile): then_dirty_tiles = [then_dirty_tiles] for tile in then_dirty_tiles: if not self.amount > self.dirt_properties.max_global_amount: dirt = self.by_pos(tile.pos) if dirt is None: 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 dirt.set_new_amount(min(new_value, self.dirt_properties.max_local_amount)) else: return c.NOT_VALID return c.VALID def __repr__(self): s = super(DirtRegister, self).__repr__() return f'{s[:-1]}, {self.amount})' def softmax(x): """Compute softmax values for each sets of scores in x.""" e_x = np.exp(x - np.max(x)) return e_x / e_x.sum() def entropy(x): return -(x * np.log(x + 1e-8)).sum() # noinspection PyAttributeOutsideInit, PyAbstractClass class DirtFactory(BaseFactory): @property def additional_actions(self) -> Union[Action, List[Action]]: super_actions = super().additional_actions if self.dirt_prop.agent_can_interact: super_actions.append(Action(enum_ident=CLEAN_UP_ACTION)) return super_actions @property def additional_entities(self) -> Dict[(Enum, Entities)]: super_entities = super().additional_entities dirt_register = DirtRegister(self.dirt_prop, self._level_shape) super_entities.update(({c.DIRT: dirt_register})) return super_entities def __init__(self, *args, dirt_prop: DirtProperties = DirtProperties(), env_seed=time.time_ns(), **kwargs): if isinstance(dirt_prop, dict): dirt_prop = DirtProperties(**dirt_prop) self.dirt_prop = dirt_prop self._dirt_rng = np.random.default_rng(env_seed) self._dirt: DirtRegister kwargs.update(env_seed=env_seed) super().__init__(*args, **kwargs) def render_additional_assets(self, mode='human'): additional_assets = super().render_additional_assets() dirt = [RenderEntity('dirt', dirt.tile.pos, min(0.15 + dirt.amount, 1.5), 'scale') for dirt in self[c.DIRT]] additional_assets.extend(dirt) return additional_assets def clean_up(self, agent: Agent) -> c: if dirt := self[c.DIRT].by_pos(agent.pos): new_dirt_amount = dirt.amount - self.dirt_prop.clean_amount if new_dirt_amount <= 0: self[c.DIRT].delete_env_object(dirt) else: dirt.set_new_amount(max(new_dirt_amount, c.FREE_CELL.value)) return c.VALID else: return c.NOT_VALID def trigger_dirt_spawn(self, initial_spawn=False): dirt_rng = self._dirt_rng free_for_dirt = [x for x in self[c.FLOOR] if len(x.guests) == 0 or (len(x.guests) == 1 and isinstance(next(y for y in x.guests), Dirt)) ] self._dirt_rng.shuffle(free_for_dirt) if initial_spawn: var = self.dirt_prop.initial_dirt_spawn_r_var new_spawn = self.dirt_prop.initial_dirt_ratio + dirt_rng.uniform(-var, var) else: new_spawn = dirt_rng.uniform(0, self.dirt_prop.max_spawn_ratio) n_dirt_tiles = max(0, int(new_spawn * len(free_for_dirt))) self[c.DIRT].spawn_dirt(free_for_dirt[:n_dirt_tiles]) def do_additional_step(self) -> dict: info_dict = super().do_additional_step() if smear_amount := self.dirt_prop.dirt_smear_amount: for agent in self[c.AGENT]: if agent.temp_valid and agent.last_pos != c.NO_POS: if self._actions.is_moving_action(agent.temp_action): if old_pos_dirt := self[c.DIRT].by_pos(agent.last_pos): if smeared_dirt := round(old_pos_dirt.amount * smear_amount, 2): old_pos_dirt.set_new_amount(max(0, old_pos_dirt.amount-smeared_dirt)) if new_pos_dirt := self[c.DIRT].by_pos(agent.pos): new_pos_dirt.set_new_amount(max(0, new_pos_dirt.amount + smeared_dirt)) else: if self[c.DIRT].spawn_dirt(agent.tile): new_pos_dirt = self[c.DIRT].by_pos(agent.pos) new_pos_dirt.set_new_amount(max(0, new_pos_dirt.amount + smeared_dirt)) if self._next_dirt_spawn < 0: pass # No Dirt Spawn elif not self._next_dirt_spawn: self.trigger_dirt_spawn() self._next_dirt_spawn = self.dirt_prop.spawn_frequency else: self._next_dirt_spawn -= 1 return info_dict def do_additional_actions(self, agent: Agent, action: Action) -> Union[None, c]: valid = super().do_additional_actions(agent, action) if valid is None: if action == CLEAN_UP_ACTION: if self.dirt_prop.agent_can_interact: valid = self.clean_up(agent) return valid else: return c.NOT_VALID else: return None else: return valid def do_additional_reset(self) -> None: super().do_additional_reset() self.trigger_dirt_spawn(initial_spawn=True) self._next_dirt_spawn = self.dirt_prop.spawn_frequency if self.dirt_prop.spawn_frequency else -1 def check_additional_done(self): super_done = super().check_additional_done() 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]] current_dirt_amount = sum(dirt) dirty_tile_count = len(dirt) # if dirty_tile_count: # dirt_distribution_score = entropy(softmax(np.asarray(dirt)) / dirty_tile_count) #else: # dirt_distribution_score = 0 info_dict.update(dirt_amount=current_dirt_amount) info_dict.update(dirty_tile_count=dirty_tile_count) # info_dict.update(dirt_distribution_score=dirt_distribution_score) if agent.temp_action == CLEAN_UP_ACTION: if agent.temp_valid: # Reward if pickup succeds, # 0.5 on every pickup reward += 0.5 info_dict.update(dirt_cleaned=1) if self.dirt_prop.done_when_clean and (len(self[c.DIRT]) == 0): # 0.5 additional reward for the very last pickup reward += 4.5 info_dict.update(done_clean=1) self.print(f'{agent.name} did just clean up some dirt at {agent.pos}.') else: reward -= 0.01 self.print(f'{agent.name} just tried to clean up some dirt at {agent.pos}, but failed.') info_dict.update({f'{agent.name}_failed_dirt_cleanup': 1}) info_dict.update(failed_dirt_clean=1) # Potential based rewards -> # track the last reward , minus the current reward = potential return reward, info_dict if __name__ == '__main__': from environments.utility_classes import AgentRenderOptions as ARO render = True dirt_props = DirtProperties( initial_dirt_ratio=0.35, initial_dirt_spawn_r_var=0.1, clean_amount=0.34, max_spawn_amount=0.1, max_global_amount=20, max_local_amount=1, spawn_frequency=0, max_spawn_ratio=0.05, dirt_smear_amount=0.0, agent_can_interact=True ) obs_props = ObservationProperties(render_agents=ARO.COMBINED, omit_agent_self=True, 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=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 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() # 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