def __init__(self, maze_size, maze_kind, goal_fixed, maze_fixed,
goal_reward, wall_reward, **kwargs):
super().__init__()
self.size = maze_size
self.kind = maze_kind
self.maze_fixed = maze_fixed
self.goal_fixed = goal_fixed
self.goal_reward = goal_reward
self.wall_reward = wall_reward
if self.maze_fixed and self.kind == "maze":
file = pkg_resources.resource_filename(
"rl_trickery",
"envs/mazes/raw_maze_{}.npy".format(int(self.size)))
array = np.load(file)
self.maze = Maze("empty", 8).from_numpy(array)
else:
self.maze = Maze(self.kind, self.size)
if self.goal_fixed:
self.maze.default_goal()
self.motions = VonNeumannMotion()
self.observation_space = Box(low=0,
high=255,
shape=list(self.maze.size) + [3],
dtype=np.uint8)
self.action_space = Discrete(len(self.motions))
def __init__(self):
super().__init__()
# # Run by run env variables
self.robber_start_idx = [[3, 3]]
self.maze = SoloMaze()
self.motions = VonNeumannMotion()
self.observation_space = Box(low=0, high=len(self.maze.objects), shape=self.maze.size, dtype=np.uint8)
self.action_space = Discrete(len(self.motions))
# Players lists for grouping
self.players = [self.maze.objects.robber]
self.robber_list = [self.maze.objects.robber]
def __init__(self):
super(EightRooms, self).__init__()
self.maze = Maze()
self.motions = VonNeumannMotion()
self.start_idx = []
for i in range(ROOMS - 7):
self.start_idx.append([[3, 3, i]])
self.goal_idx = [[WIDTH - 2, WIDTH - 2, ROOMS - 1]]
self.width = WIDTH
self.rooms = ROOMS
self.observation_space = Box(low=0,
high=np.max([WIDTH, ROOMS]),
shape=np.array(self.start_idx[0]).shape,
dtype=np.uint8)
self.action_space = Discrete(len(self.motions))
self.steps = 0
def __init__(self, maze):
"""
https://github.com/zuoxingdong/mazelab
https://github.com/zuoxingdong/mazelab/blob/master/examples/navigation_env.ipynb
"""
super().__init__()
self.reward = None
self.stepcost = None
self.maze = maze
self.motions = VonNeumannMotion()
self.actions = [(0, 1), (1, 0), (0, -1),
(-1, 0)] # NORTH, EAST, SOUTH, WEST
self.observation_space = Box(low=0,
high=len(self.maze.objects),
shape=self.maze.size,
dtype=np.uint8)
self.action_space = Discrete(len(self.motions))
# viz properties
self.env_lw = 2
def __init__(self, agent_num):
super().__init__()
self.agent_num = agent_num
self.maze = MAMaze(self.agent_num)
self.gt_global_map = self.maze.to_value()
self.motions = VonNeumannMotion()
self.observation_space = Box(low=0,
high=len(self.maze.objects),
shape=self.maze.size,
dtype=np.uint8)
self.action_space = Discrete(len(self.motions))
self.global_map_size = 60
self.local_map_size = 11
self.global_map = np.full((self.global_map_size, self.global_map_size),
-1)
self.step_n = 5
self.episode_length = 5