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from __future__ import annotationsfrom minigrid.core.grid import Gridfrom minigrid.core.mission import MissionSpacefrom minigrid.core.world_object import ( SlipperyEast, SlipperySouth, SlipperyNorth, SlipperyWest, SlipperyNorthEast, Lava, Goal )from minigrid.envs.adversaries_base import AdversaryEnvfrom minigrid.core.tasks import FollowAgent, DoRandom, GoTo
from minigrid.minigrid_env import MiniGridEnv, is_slippery
import numpy as npfrom itertools import product
class WindyCityEnv(MiniGridEnv): def __init__(self, randomize_start=True, size=10, width=24, height=22, probability_intended=8/9, probability_turn_intended=8/9, obstacle_type=Lava, goal_reward=1, failure_penalty=-1, per_step_penalty=0, dense_rewards=False, **kwargs):
self.obstacle_type = obstacle_type self.size = size self.probability_intended = probability_intended self.probability_turn_intended = probability_turn_intended
if width is not None and height is not None: self.width = width self.height = height elif size is not None: self.width = size self.height = size else: raise ValueError(f"Please define either width and height or a size for square environments. The set values are width: {width}, height: {height}, size: {size}.")
mission_space = MissionSpace(mission_func=self._gen_mission) super().__init__( width=self.width, height=self.height, max_steps=200, # Set this to True for maximum speed see_through_walls=False, mission_space = mission_space, **kwargs )
self.randomize_start = randomize_start self.goal_reward = goal_reward self.failure_penalty = failure_penalty self.dense_rewards = dense_rewards self.per_step_penalty = per_step_penalty
self.trajectory = list()
@staticmethod def _gen_mission(): return "Finish your task while avoiding the adversaries"
def disable_random_start(self): self.randomize_start = False
def place_agent(self, spawn_on_slippery=False, agent_pos=None, agent_dir=0): max_tries = 10_000 num_tries = 0
if self.randomize_start == True: while True: num_tries += 1 if num_tries > max_tries: raise RecursionError("rejection sampling failed in place_obj") x = np.random.randint(0, self.width) y = np.random.randint(0, self.height)
cell = self.grid.get(*(x,y)) if ( cell is None or (cell.can_overlap() and not isinstance(cell, Lava) and not isinstance(cell, Goal) and (spawn_on_slippery or not is_slippery(cell)) and not (x in [7, 8, 9, 10] and y in [9, 10])) ): self.agent_pos = np.array((x, y)) self.agent_dir = np.random.randint(0, 4) break elif agent_dir is None: self.agent_pos = np.array((1, 1)) self.agent_dir = 0 else: self.agent_pos = agent_pos self.agent_dir = agent_dir self.trajectory.append((self.agent_pos, self.agent_dir))
def place_goal(self, goal_pos): self.goal_pos = goal_pos self.put_obj(Goal(), *self.goal_pos)
def printGrid(self, init=False): grid = super().printGrid(init)
properties_str = ""
properties_str += F"ProbTurnIntended:{self.probability_turn_intended}\n" properties_str += F"ProbForwardIntended:{self.probability_intended}\n"
return grid + properties_str
def step(self, action): obs, reward, terminated, truncated, info = super().step(action) self.trajectory.append((action, self.agent_pos, self.agent_dir)) if truncated and info["ran_into_lava"]: print(self.trajectory) print("truncated: ", info) self.trajectory = list() if truncated and info["reached_goal"]: print("truncated: ", info) self.trajectory = list() elif terminated and info["ran_into_lava"]: print(self.trajectory) print("terminated: ", info) self.trajectory = list() elif terminated: print("terminated: ", info) self.trajectory = list() elif truncated: print("truncated: ", info) self.trajectory = list() return obs, reward - self.per_step_penalty, terminated, truncated, info
def reset(self, **kwargs) -> tuple[ObsType, dict[str, Any]]: return super().reset(**kwargs)
def _place_building(self, col, row, width, height, obj_type=Lava): for i in range(col, width + col): self.grid.vert_wall(i, row, height, obj_type=obj_type)
def _gen_grid(self, width, height): super()._gen_grid(width, height) self.grid = Grid(width, height)
# Generate the surrounding walls self.grid.horz_wall(0, 0) self.grid.horz_wall(0, height - 1) self.grid.vert_wall(0, 0) self.grid.vert_wall(width - 1, 0)
for i in range(1, height - 1): self.grid.horz_wall(1, i, width-2, obj_type=SlipperyNorthEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(13, 1, 4, 2) self.grid.vert_wall(12, 1, 2, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(13, 3, 4, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(17, 1, 2, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(7, 3, 3, 4) self.grid.vert_wall(6, 3, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(10, 3, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(7, 2, 3, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(7, 7, 3, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(15, 7, 6, 4) self.grid.vert_wall(14, 7, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(14, 9, 2, obj_type=Lava) self.grid.vert_wall(20, 7, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(13, 9, 2, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(15, 6, 5, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(14, 11, 6, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(5, 11, 5, 6) self.grid.vert_wall(4, 11, 6, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(10, 11, 6, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(5, 17, 5, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(5, 10, 5, obj_type=SlipperyWest("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(6, 9, 4, obj_type=SlipperyWest("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(9, 7, 4, obj_type=SlipperySouth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(21, 13, 2, 5) self.grid.vert_wall(20, 13, 5, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(21, 12, 2, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(21, 18, 2, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self.place_agent(agent_pos=np.array((1, height -2)), agent_dir=0, spawn_on_slippery=True) self.place_goal(np.array((width - 2, 1))) if self.dense_rewards: self.run_bfs()
class WindyCityAdvEnv(AdversaryEnv): def __init__(self, randomize_start=True, size=10, width=15, height=15, probability_intended=8/9, probability_turn_intended=8/9, obstacle_type=Lava, goal_reward=1, failure_penalty=-1, per_step_penalty=0, dense_rewards=False, **kwargs):
self.obstacle_type = obstacle_type self.size = size self.probability_intended = probability_intended self.probability_turn_intended = probability_turn_intended
if width is not None and height is not None: self.width = width self.height = height elif size is not None: self.width = size self.height = size else: raise ValueError(f"Please define either width and height or a size for square environments. The set values are width: {width}, height: {height}, size: {size}.")
super().__init__( width=self.width, height=self.height, max_steps=200, # Set this to True for maximum speed see_through_walls=False, **kwargs )
self.randomize_start = randomize_start self.goal_reward = goal_reward self.failure_penalty = failure_penalty self.dense_rewards = dense_rewards self.per_step_penalty = per_step_penalty
self.trajectory = list()
def disable_random_start(self): self.randomize_start = False
def place_agent(self, spawn_on_slippery=False, agent_pos=None, agent_dir=0): max_tries = 10_000 num_tries = 0
if self.randomize_start == True: while True: num_tries += 1 if num_tries > max_tries: raise RecursionError("rejection sampling failed in place_obj") x = np.random.randint(0, self.width) y = np.random.randint(0, self.height)
cell = self.grid.get(*(x,y)) if ( cell is None or (cell.can_overlap() and not isinstance(cell, Lava) and not isinstance(cell, Goal) and (spawn_on_slippery or not is_slippery(cell)) and not (x in [7, 8, 9, 10] and y in [9, 10])) ): self.agent_pos = np.array((x, y)) self.agent_dir = np.random.randint(0, 4) break elif agent_dir is None: self.agent_pos = np.array((1, 1)) self.agent_dir = 0 else: self.agent_pos = agent_pos self.agent_dir = agent_dir self.trajectory.append((self.agent_pos, self.agent_dir))
def place_goal(self, goal_pos): self.goal_pos = goal_pos self.put_obj(Goal(), *self.goal_pos)
def printGrid(self, init=False): grid = super().printGrid(init)
properties_str = ""
properties_str += F"ProbTurnIntended:{self.probability_turn_intended}\n" properties_str += F"ProbForwardIntended:{self.probability_intended}\n"
return grid + properties_str
def step(self, action): obs, reward, terminated, truncated, info = super().step(action) self.trajectory.append((action, self.agent_pos, self.agent_dir, str(self.adversaries["blue"]))) if truncated and info["ran_into_lava"]: print(self.trajectory) print("truncated: ", info) self.trajectory = list() if truncated and info["reached_goal"]: print("truncated: ", info) self.trajectory = list() elif terminated and info["ran_into_lava"]: print(self.trajectory) print("terminated: ", info) self.trajectory = list() elif terminated: print("terminated: ", info) self.trajectory = list() elif truncated: print("truncated: ", info) self.trajectory = list() return obs, reward - self.per_step_penalty, terminated, truncated, info
def reset(self, **kwargs) -> tuple[ObsType, dict[str, Any]]: return super().reset(**kwargs)
def _place_building(self, col, row, width, height, obj_type=Lava): for i in range(col, width + col): self.grid.vert_wall(i, row, height, obj_type=obj_type)
def _gen_grid(self, width, height): super()._gen_grid(width, height) self.grid = Grid(width, height)
# Generate the surrounding walls self.grid.horz_wall(0, 0) self.grid.horz_wall(0, height - 1) self.grid.vert_wall(0, 0) self.grid.vert_wall(width - 1, 0)
for i in range(1, height - 1): self.grid.horz_wall(1, i, width-2, obj_type=SlipperyNorthEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(7, 1, 4, 1) self.grid.vert_wall(6, 1, 1, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(7, 2, 4, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(11, 1, 1, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(4, 5, 2, 1) self.grid.vert_wall(3, 5, 1, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(6, 5, 1, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(4, 4, 2, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(4, 6, 2, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(12, 7, 2, 3) self.grid.vert_wall(11, 7, 3, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(11, 6, 3, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(11, 10, 3, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(4, 10, 2, 2) self.grid.vert_wall(3, 10, 2, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(6, 10, 2, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(4, 12, 2, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(4, 9, 2, obj_type=SlipperyWest("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(5, 7, 3, obj_type=SlipperySouth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
#should spawn randomly x = np.random.choice([1,2,3,6,7,8,9]) y = np.random.choice([6,7,8]) self.add_adversary(x, y, "blue", direction=1, tasks=[FollowAgent("red", duration=2), DoRandom(duration=2)], repeating=True)
self.place_agent(agent_pos=np.array((1, height -2)), agent_dir=0, spawn_on_slippery=True) self.place_goal(np.array((width - 2, 1))) if self.dense_rewards: self.run_bfs()
class WindyCity2Env(MiniGridEnv): def __init__(self, randomize_start=True, size=10, width=27, height=22, probability_intended=8/9, probability_turn_intended=8/9, obstacle_type=Lava, goal_reward=1, failure_penalty=-1, per_step_penalty=0, dense_rewards=False, two_player_winning_region_start=False, **kwargs):
self.obstacle_type = obstacle_type self.size = size self.probability_intended = probability_intended self.probability_turn_intended = probability_turn_intended
if width is not None and height is not None: self.width = width self.height = height elif size is not None: self.width = size self.height = size else: raise ValueError(f"Please define either width and height or a size for square environments. The set values are width: {width}, height: {height}, size: {size}.")
mission_space = MissionSpace(mission_func=self._gen_mission) super().__init__( width=self.width, height=self.height, max_steps=200, # Set this to True for maximum speed see_through_walls=False, mission_space = mission_space, **kwargs )
self.randomize_start = randomize_start self.two_player_winning_region_start = two_player_winning_region_start self.goal_reward = goal_reward self.failure_penalty = failure_penalty self.dense_rewards = dense_rewards self.per_step_penalty = per_step_penalty
self.trajectory = list()
@staticmethod def _gen_mission(): return "Finish your task while avoiding the adversaries"
def disable_random_start(self): self.randomize_start = False
def place_agent(self, spawn_on_slippery=False, agent_pos=None, agent_dir=0): max_tries = 10_000 num_tries = 0
if self.two_player_winning_region_start == True: winning_region = list() winning_region += product([1,2,3,4], [y for y in range(1, self.height-1)]) winning_region += product([x for x in range(1,12)], [1]) winning_region += product([x for x in range(1,self.width-10)], [self.height-2]) winning_region += product([x for x in range(self.width-6, self.width-1)], [1,2,3,4]) winning_region += product([x for x in range(self.width-11, self.width-1)], [5]) x, y= winning_region[np.random.choice(len(winning_region), 1)[0]] self.agent_pos = np.array((x,y)) self.agent_dir = np.random.randint(0, 4) self.trajectory.append((self.agent_pos, self.agent_dir)) return
if self.randomize_start == True: while True: num_tries += 1 if num_tries > max_tries: raise RecursionError("rejection sampling failed in place_obj") x = np.random.randint(0, self.width) y = np.random.randint(0, self.height)
cell = self.grid.get(*(x,y)) if ( cell is None or (cell.can_overlap() and not isinstance(cell, Lava) and not isinstance(cell, Goal) and (spawn_on_slippery or not is_slippery(cell)) and not (x in [7, 8, 9, 10] and y in [9, 10])) ): self.agent_pos = np.array((x, y)) self.agent_dir = np.random.randint(0, 4) break elif agent_dir is None: self.agent_pos = np.array((1, 1)) self.agent_dir = 0 else: self.agent_pos = agent_pos self.agent_dir = agent_dir self.trajectory.append((self.agent_pos, self.agent_dir))
def place_goal(self, goal_pos): self.goal_pos = goal_pos self.put_obj(Goal(), *self.goal_pos)
def printGrid(self, init=False): grid = super().printGrid(init)
properties_str = ""
properties_str += F"ProbTurnIntended:{self.probability_turn_intended}\n" properties_str += F"ProbForwardIntended:{self.probability_intended}\n"
return grid + properties_str
def step(self, action): obs, reward, terminated, truncated, info = super().step(action) self.trajectory.append((action, self.agent_pos, self.agent_dir)) if truncated and info["ran_into_lava"]: print(self.trajectory) print("truncated: ", info) self.trajectory = list() if truncated and info["reached_goal"]: print("truncated: ", info) self.trajectory = list() elif terminated and info["ran_into_lava"]: print(self.trajectory) print("terminated: ", info) self.trajectory = list() elif terminated: print("terminated: ", info) self.trajectory = list() elif truncated: print("truncated: ", info) self.trajectory = list() return obs, reward - self.per_step_penalty, terminated, truncated, info
def reset(self, **kwargs) -> tuple[ObsType, dict[str, Any]]: return super().reset(**kwargs)
def _place_building(self, col, row, width, height, obj_type=Lava): for i in range(col, width + col): self.grid.vert_wall(i, row, height, obj_type=obj_type)
def _gen_grid(self, width, height): super()._gen_grid(width, height) self.grid = Grid(width, height)
# Generate the surrounding walls self.grid.horz_wall(0, 0) self.grid.horz_wall(0, height - 1) self.grid.vert_wall(0, 0) self.grid.vert_wall(width - 1, 0)
for i in range(1, height - 1): self.grid.horz_wall(1, i, width-2, obj_type=SlipperyNorthEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self.grid.horz_wall(1, 17, 15, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(1, 18, 16, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(1, 19, 17, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(1, 20, 18, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self.grid.horz_wall(1, 7, 9, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(1, 8, 8, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(1, 9, 8, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(1, 10, 7, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(16, 1, 4, 2) self.grid.vert_wall(15, 1, 2, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(16, 3, 4, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(20, 1, 2, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(10, 3, 3, 4) #self.grid.vert_wall(9, 3, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(13, 3, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(10, 2, 3, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(10, 7, 3, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(16, 7, 8, 5) self.grid.vert_wall(15, 7, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) #self.grid.vert_wall(17, 9, 3, obj_type=Lava) self.grid.vert_wall(24, 7, 5, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(15, 9, 3, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(16, 6, 7, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(16, 12, 7, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(22, 12, 1, obj_type=SlipperyNorthEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(23, 13, 1, obj_type=SlipperyNorthEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(8, 11, 5, 6) #self.grid.vert_wall(7, 11, 6, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(13, 11, 6, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(8, 17, 5, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(9, 10, 4, obj_type=SlipperyWest("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(10, 9, 3, obj_type=SlipperyWest("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.vert_wall(12, 7, 4, obj_type=SlipperySouth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self._place_building(22, 14, 4, 4) self.grid.vert_wall(21, 14, 4, obj_type=SlipperyNorth("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(22, 13, 4, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended)) self.grid.horz_wall(22, 18, 4, obj_type=SlipperyEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
#self.grid.vert_wall(22, 13, 1, obj_type=SlipperyNorthEast("white", probability_intended=self.probability_intended, probability_turn_intended=self.probability_turn_intended))
self.place_agent(agent_pos=np.array((18, height - 4)), agent_dir=3, spawn_on_slippery=True) self.place_goal(np.array((width - 2, 10))) if self.dense_rewards: self.run_bfs()
class WindyCitySmallAdv(AdversaryEnv): def __init__(self, randomize_start=True, size=10, width=11, height=9, probability_intended=1, probability_turn_intended=1, obstacle_type=Lava, goal_reward=1, failure_penalty=-1, per_step_penalty=0, dense_rewards=False, two_player_winning_region_start=False, **kwargs):
self.obstacle_type = obstacle_type self.size = size self.probability_intended = probability_intended self.probability_turn_intended = probability_turn_intended
if width is not None and height is not None: self.width = width self.height = height elif size is not None: self.width = size self.height = size else: raise ValueError(f"Please define either width and height or a size for square environments. The set values are width: {width}, height: {height}, size: {size}.")
mission_space = MissionSpace(mission_func=self._gen_mission) super().__init__( width=self.width, height=self.height, max_steps=50, # Set this to True for maximum speed see_through_walls=False, #mission_space = mission_space, **kwargs )
self.randomize_start = randomize_start self.two_player_winning_region_start = two_player_winning_region_start self.goal_reward = goal_reward self.failure_penalty = failure_penalty self.dense_rewards = dense_rewards self.per_step_penalty = per_step_penalty
self.trajectory = list()
@staticmethod def _gen_mission(): return "Finish your task while avoiding the adversaries"
def disable_random_start(self): self.randomize_start = False
def place_agent(self, spawn_on_slippery=False, agent_pos=None, agent_dir=0): max_tries = 10_000 num_tries = 0
if self.randomize_start == True: while True: num_tries += 1 if num_tries > max_tries: raise RecursionError("rejection sampling failed in place_obj") x = np.random.randint(0, self.width) y = np.random.randint(5, self.height)
cell = self.grid.get(*(x,y)) if ( cell is None or (cell.can_overlap() and not isinstance(cell, Lava) and not isinstance(cell, Goal) and (spawn_on_slippery or not is_slippery(cell)) and not (x in [7, 8, 9, 10] and y in [9, 10])) ): self.agent_pos = np.array((x, y)) self.agent_dir = np.random.randint(0, 4) break elif agent_dir is None: self.agent_pos = np.array((1, 1)) self.agent_dir = 0 else: self.agent_pos = agent_pos self.agent_dir = agent_dir self.trajectory.append((self.agent_pos, self.agent_dir))
def place_goal(self, goal_pos): self.goal_pos = goal_pos self.put_obj(Goal(), *self.goal_pos)
def printGrid(self, init=False): grid = super().printGrid(init)
properties_str = ""
properties_str += F"ProbTurnIntended:{self.probability_turn_intended}\n" properties_str += F"ProbForwardIntended:{self.probability_intended}\n"
return grid + properties_str
def step(self, action): obs, reward, terminated, truncated, info = super().step(action) self.trajectory.append((action, self.agent_pos, self.agent_dir)) if truncated and info["ran_into_lava"]: print(self.trajectory) print("truncated: ", info) self.trajectory = list() if truncated and info["reached_goal"]: print("truncated: ", info) self.trajectory = list() elif terminated and info["ran_into_lava"]: print(self.trajectory) print("terminated: ", info) self.trajectory = list() elif terminated and info["collision"]: print(self.trajectory) print("terminated: ", info) self.trajectory = list() elif terminated: print("terminated: ", info) self.trajectory = list() elif truncated: print("truncated: ", info) self.trajectory = list() return obs, reward - self.per_step_penalty, terminated, truncated, info
def reset(self, **kwargs) -> tuple[ObsType, dict[str, Any]]: return super().reset(**kwargs)
def _place_building(self, col, row, width, height, obj_type=Lava): for i in range(col, width + col): self.grid.vert_wall(i, row, height, obj_type=obj_type)
def _gen_grid(self, width, height): super()._gen_grid(width, height) self.grid = Grid(width, height)
# Generate the surrounding walls self.grid.horz_wall(0, 0) self.grid.horz_wall(0, height - 1) self.grid.vert_wall(0, 0) self.grid.vert_wall(width - 1, 0)
self._place_building(3, 3, 5, 2) blue_adv = self.add_adversary(2, 4, "blue", direction=3, tasks= [GoTo((2,2)), GoTo((8,2)), GoTo((8,4)), GoTo((8,2)), GoTo((2,2)), GoTo((2,4))], repeating=True)
self.place_agent(agent_pos=np.array((5, 5)), agent_dir=3, spawn_on_slippery=True) self.place_goal(np.array((width//2, 1))) if self.dense_rewards: self.run_bfs()
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