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' )