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from gym_minigrid.minigrid import *
from gym_minigrid.register import register
class Guide(NPC):
"""
A simple NPC that wants an agent to go to an object (randomly chosen among object_pos list)
"""
def __init__(self, color, name, env):
super().__init__(color)
self.name = name
self.env = env
self.has_spoken = False # wizards only speak once
self.npc_type = 0
def listen(self, utterance):
if utterance == TalkHardSesameGrammar.construct_utterance([0, 1]):
return self.env.mission
return None
# def is_near_agent(self):
# ax, ay = self.env.agent_pos
# wx, wy = self.cur_pos
# if (ax == wx and abs(ay - wy) == 1) or (ay == wy and abs(ax - wx) == 1):
# return True
# return False
class TalkHardSesameGrammar(object):
templates = ["Where is", "Open"]
things = ["sesame", "the exit"]
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 GoToDoorTalkHardNPCEnv(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,
hear_yourself=False,
diminished_reward=True,
step_penalty=False
):
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),
*TalkHardSesameGrammar.grammar_action_space.nvec
])
)
self.hear_yourself = hear_yourself
self.diminished_reward = diminished_reward
self.step_penalty = step_penalty
self.empty_symbol = "NA \n"
print({
"size": size,
"hear_yourself": hear_yourself,
"diminished_reward": diminished_reward,
"step_penalty": step_penalty,
})
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 surrounding walls
self.grid.wall_rect(0, 0, width, height)
# Generate the 4 doors at random positions
self.door_pos = []
self.door_front_pos = [] # Remembers positions in front of door to avoid setting wizard here
self.door_pos.append((self._rand_int(2, width-2), 0))
self.door_front_pos.append((self.door_pos[-1][0], self.door_pos[-1][1]+1))
self.door_pos.append((self._rand_int(2, width-2), height-1))
self.door_front_pos.append((self.door_pos[-1][0], self.door_pos[-1][1] - 1))
self.door_pos.append((0, self._rand_int(2, height-2)))
self.door_front_pos.append((self.door_pos[-1][0] + 1, self.door_pos[-1][1]))
self.door_pos.append((width-1, self._rand_int(2, height-2)))
self.door_front_pos.append((self.door_pos[-1][0] - 1, self.door_pos[-1][1]))
# Generate the door colors
self.door_colors = []
while len(self.door_colors) < len(self.door_pos):
color = self._rand_elem(COLOR_NAMES)
if color in self.door_colors:
continue
self.door_colors.append(color)
# Place the doors in the grid
for idx, pos in enumerate(self.door_pos):
color = self.door_colors[idx]
self.grid.set(*pos, Door(color))
# Set a randomly coloured NPC at a random position
color = self._rand_elem(COLOR_NAMES)
self.wizard = Guide(color, "Gandalf", self)
# Place it randomly, omitting front of door positions
self.place_obj(self.wizard,
size=(width, height),
reject_fn=lambda _, p: tuple(p) in self.door_front_pos)
# Randomize the agent start position and orientation
self.place_agent(size=(width, height))
# Select a random target door
self.doorIdx = self._rand_int(0, len(self.door_pos))
self.target_pos = self.door_pos[self.doorIdx]
self.target_color = self.door_colors[self.doorIdx]
# Generate the mission string
self.mission = 'go to the %s door' % self.target_color
# Dummy beginning string
self.beginning_string = "This is what you hear. \n"
self.utterance = self.beginning_string
# utterance appended at the end of each step
self.utterance_history = ""
def step(self, action):
p_action = action[0]
utterance_action = action[1:]
# assert all nan or neither nan
assert len(set(np.isnan(utterance_action))) == 1
speak_flag = not all(np.isnan(utterance_action))
obs, reward, done, info = super().step(p_action)
if speak_flag:
agent_utterance = TalkHardSesameGrammar.construct_utterance(utterance_action)
if self.hear_yourself:
self.utterance += "YOU: {} \n".format(agent_utterance)
# check if near wizard
if self.wizard.is_near_agent():
reply = self.wizard.listen(agent_utterance)
if reply:
self.utterance += "{}: {} \n".format(self.wizard.name, reply)
# Don't let the agent open any of the doors
if p_action == self.actions.toggle:
done = True
if p_action == self.actions.done:
ax, ay = self.agent_pos
tx, ty = self.target_pos
if (ax == tx and abs(ay - ty) == 1) or (ay == ty and abs(ax - tx) == 1):
reward = self._reward()
done = True
# discount
if self.step_penalty:
reward = reward - 0.01
# fill observation with text
self.append_existing_utterance_to_history()
obs = self.add_utterance_to_observation(obs)
self.reset_utterance()
return obs, reward, done, info
def _reward(self):
if self.diminished_reward:
return super()._reward()
else:
return 1.0
def render(self, *args, **kwargs):
obs = super().render(*args, **kwargs)
self.window.set_caption(self.utterance_history, [
"Gandalf:",
"Jack:",
"John:",
"Where is the exit",
"Open sesame",
])
return obs
class GoToDoorTalkHardNPCTesting(GoToDoorTalkHardNPCEnv):
def __init__(self):
super().__init__(
size=5,
hear_yourself=False,
diminished_reward=False,
step_penalty=True
)
class GoToDoorTalkHardNPC8x8Env(GoToDoorTalkHardNPCEnv):
def __init__(self):
super().__init__(size=8)
class GoToDoorTalkHardNPC6x6Env(GoToDoorTalkHardNPCEnv):
def __init__(self):
super().__init__(size=6)
# hear yourself
class GoToDoorTalkHardNPCHY8x8Env(GoToDoorTalkHardNPCEnv):
def __init__(self):
super().__init__(size=8, hear_yourself=True)
class GoToDoorTalkHardNPCHY6x6Env(GoToDoorTalkHardNPCEnv):
def __init__(self):
super().__init__(size=6, hear_yourself=True)
class GoToDoorTalkHardNPCHY5x5Env(GoToDoorTalkHardNPCEnv):
def __init__(self):
super().__init__(size=5, hear_yourself=True)
register(
id='MiniGrid-GoToDoorTalkHardNPC-Testing-v0',
entry_point='gym_minigrid.envs:GoToDoorTalkHardNPCTesting'
)
register(
id='MiniGrid-GoToDoorTalkHardNPC-5x5-v0',
entry_point='gym_minigrid.envs:GoToDoorTalkHardNPCEnv'
)
register(
id='MiniGrid-GoToDoorTalkHardNPC-6x6-v0',
entry_point='gym_minigrid.envs:GoToDoorTalkHardNPC6x6Env'
)
register(
id='MiniGrid-GoToDoorTalkHardNPC-8x8-v0',
entry_point='gym_minigrid.envs:GoToDoorTalkHardNPC8x8Env'
)
register(
id='MiniGrid-GoToDoorTalkHardNPCHY-5x5-v0',
entry_point='gym_minigrid.envs:GoToDoorTalkHardNPCHY5x5Env'
)
register(
id='MiniGrid-GoToDoorTalkHardNPCHY-6x6-v0',
entry_point='gym_minigrid.envs:GoToDoorTalkHardNPCHY6x6Env'
)
register(
id='MiniGrid-GoToDoorTalkHardNPCHY-8x8-v0',
entry_point='gym_minigrid.envs:GoToDoorTalkHardNPCHY8x8Env'
)
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