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from gym_minigrid.minigrid import *
from gym_minigrid.register import register
class SesameGrammar(object):
templates = ["Open", "Who is", "Where is"]
things = ["the exit", "sesame", "the chest", "him", "that"]
grammar_action_space = spaces.MultiDiscrete([len(templates), len(things)])
@classmethod
def construct_utterance(cls, action):
return cls.templates[int(action[0])] + " " + cls.things[int(action[1])] + "."
class GoToDoorSesameEnv(MultiModalMiniGridEnv):
"""
Environment in which the agent is instructed to go to a given object
named using an English text string
"""
def __init__(
self,
size=5
):
assert size >= 5
super().__init__(
grid_size=size,
max_steps=5*size**2,
# Set this to True for maximum speed
see_through_walls=True,
actions=MiniGridEnv.Actions,
action_space=spaces.MultiDiscrete([
len(MiniGridEnv.Actions),
*SesameGrammar.grammar_action_space.nvec
])
)
def _gen_grid(self, width, height):
# Create the grid
self.grid = Grid(width, height)
# Randomly vary the room width and height
width = self._rand_int(5, width+1)
height = self._rand_int(5, height+1)
# Generate the surrounding walls
self.grid.wall_rect(0, 0, width, height)
# Generate the 4 doors at random positions
doorPos = (self._rand_int(2, width-2), 0)
doorColors = self._rand_elem(COLOR_NAMES)
self.grid.set(*doorPos, Door(doorColors))
# doorPos = []
# doorPos.append((self._rand_int(2, width-2), 0))
#
# # Generate the door colors
# doorColors = []
# while len(doorColors) < len(doorPos):
# color = self._rand_elem(COLOR_NAMES)
# if color in doorColors:
# continue
# doorColors.append(color)
#
# # Place the doors in the grid
# for idx, pos in enumerate(doorPos):
# color = doorColors[idx]
# self.grid.set(*pos, Door(color))
# Randomize the agent start position and orientation
self.place_agent(size=(width, height))
# Select a random target door
# doorIdx = self._rand_int(0, len(doorPos))
# self.target_pos = doorPos[doorIdx]
# self.target_color = doorColors[doorIdx]
self.target_pos = doorPos
self.target_color = doorColors
# Generate the mission string
self.mission = 'go to the %s door' % self.target_color
# Initialize the dialogue string
self.dialogue = "This is what you hear. \n"
def gen_obs(self):
obs = super().gen_obs()
# add dialogue to obs
obs["dialogue"] = self.dialogue
return obs
def step(self, action):
p_action = action[0]
utterance_action = action[1:]
assert len(set(np.isnan(utterance_action))) == 1
speak_flag = not all(np.isnan(utterance_action))
obs, reward, done, info = super().step(p_action)
ax, ay = self.agent_pos
tx, ty = self.target_pos
# Don't let the agent open any of the doors
if p_action == self.actions.toggle:
done = True
# magic words if front of the door
if speak_flag:
utterance = SesameGrammar.construct_utterance(utterance_action)
self.dialogue += "YOU: " + utterance + "\n"
if utterance == SesameGrammar.construct_utterance([0, 1]):
if (ax == tx and abs(ay - ty) == 1) or (ay == ty and abs(ax - tx) == 1):
reward = self._reward()
done = True
# Reward performing done action in front of the target door
# if p_action == self.actions.done:
# if (ax == tx and abs(ay - ty) == 1) or (ay == ty and abs(ax - tx) == 1):
# reward = self._reward()
# done = True
return obs, reward, done, info
def render(self, *args, **kwargs):
obs = super().render(*args, **kwargs)
self.window.set_caption(self.dialogue, [
"Gandalf:",
"Jack:",
"John:",
"Where is the exit",
"Open sesame",
])
return obs
class GoToDoorSesame8x8Env(GoToDoorSesameEnv):
def __init__(self):
super().__init__(size=8)
class GoToDoorSesame6x6Env(GoToDoorSesameEnv):
def __init__(self):
super().__init__(size=6)
register(
id='MiniGrid-GoToDoorSesame-5x5-v0',
entry_point='gym_minigrid.envs:GoToDoorSesameEnv'
)
register(
id='MiniGrid-GoToDoorSesame-6x6-v0',
entry_point='gym_minigrid.envs:GoToDoorSesame6x6Env'
)
register(
id='MiniGrid-GoToDoorSesame-8x8-v0',
entry_point='gym_minigrid.envs:GoToDoorSesame8x8Env'
)
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