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- from gym_minigrid.minigrid import *
- from gym_minigrid.register import register
- class MemoryEnv(MiniGridEnv):
- """
- This environment is a memory test. The agent starts in a small room
- where it sees an object. It then has to go through a narrow hallway
- which ends in a split. At each end of the split there is an object,
- one of which is the same as the object in the starting room. The
- agent has to remember the initial object, and go to the matching
- object at split.
- """
- def __init__(
- self,
- seed,
- size=8,
- random_length=False,
- ):
- self.random_length = random_length
- super().__init__(
- seed=seed,
- grid_size=size,
- max_steps=5*size**2,
- # Set this to True for maximum speed
- see_through_walls=False,
- )
- def _gen_grid(self, 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)
- assert height % 2 == 1
- upper_room_wall = height // 2 - 2
- lower_room_wall = height // 2 + 2
- if self.random_length:
- hallway_end = self._rand_int(4, width - 2)
- else:
- hallway_end = width - 3
- # Start room
- for i in range(1, 5):
- self.grid.set(i, upper_room_wall, Wall())
- self.grid.set(i, lower_room_wall, Wall())
- self.grid.set(4, upper_room_wall + 1, Wall())
- self.grid.set(4, lower_room_wall - 1, Wall())
- # Horizontal hallway
- for i in range(5, hallway_end):
- self.grid.set(i, upper_room_wall + 1, Wall())
- self.grid.set(i, lower_room_wall - 1, Wall())
- # Vertical hallway
- for j in range(0, height):
- if j != height // 2:
- self.grid.set(hallway_end, j, Wall())
- self.grid.set(hallway_end + 2, j, Wall())
- # Fix the player's start position and orientation
- self.agent_pos = (self._rand_int(1, hallway_end + 1), height // 2)
- self.agent_dir = 0
- # Place objects
- start_room_obj = self._rand_elem([Key, Ball])
- self.grid.set(1, height // 2 - 1, start_room_obj('green'))
- other_objs = self._rand_elem([[Ball, Key], [Key, Ball]])
- pos0 = (hallway_end + 1, height // 2 - 2)
- pos1 = (hallway_end + 1, height // 2 + 2)
- self.grid.set(*pos0, other_objs[0]('green'))
- self.grid.set(*pos1, other_objs[1]('green'))
- # Choose the target objects
- if start_room_obj == other_objs[0]:
- self.success_pos = (pos0[0], pos0[1] + 1)
- self.failure_pos = (pos1[0], pos1[1] - 1)
- else:
- self.success_pos = (pos1[0], pos1[1] - 1)
- self.failure_pos = (pos0[0], pos0[1] + 1)
- self.mission = 'go to the matching object at the end of the hallway'
- def step(self, action):
- if action == MiniGridEnv.Actions.pickup:
- action = MiniGridEnv.Actions.toggle
- obs, reward, done, info = MiniGridEnv.step(self, action)
- if tuple(self.agent_pos) == self.success_pos:
- reward = self._reward()
- done = True
- if tuple(self.agent_pos) == self.failure_pos:
- reward = 0
- done = True
- return obs, reward, done, info
- class MemoryS17Random(MemoryEnv):
- def __init__(self, seed=None):
- super().__init__(seed=seed, size=17, random_length=True)
- register(
- id='MiniGrid-MemoryS17Random-v0',
- entry_point='gym_minigrid.envs:MemoryS17Random',
- )
- class MemoryS13Random(MemoryEnv):
- def __init__(self, seed=None):
- super().__init__(seed=seed, size=13, random_length=True)
- register(
- id='MiniGrid-MemoryS13Random-v0',
- entry_point='gym_minigrid.envs:MemoryS13Random',
- )
- class MemoryS13(MemoryEnv):
- def __init__(self, seed=None):
- super().__init__(seed=seed, size=13)
- register(
- id='MiniGrid-MemoryS13-v0',
- entry_point='gym_minigrid.envs:MemoryS13',
- )
- class MemoryS11(MemoryEnv):
- def __init__(self, seed=None):
- super().__init__(seed=seed, size=11)
- register(
- id='MiniGrid-MemoryS11-v0',
- entry_point='gym_minigrid.envs:MemoryS11',
- )
- class MemoryS9(MemoryEnv):
- def __init__(self, seed=None):
- super().__init__(seed=seed, size=9)
- register(
- id='MiniGrid-MemoryS9-v0',
- entry_point='gym_minigrid.envs:MemoryS9',
- )
- class MemoryS7(MemoryEnv):
- def __init__(self, seed=None):
- super().__init__(seed=seed, size=7)
- register(
- id='MiniGrid-MemoryS7-v0',
- entry_point='gym_minigrid.envs:MemoryS7',
- )
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