import numpy as np from gym_minigrid.minigrid import * from gym_minigrid.register import register import time from collections import deque class Peer(NPC): """ A dancing NPC that the agent has to copy """ def __init__(self, color, name, env, knowledgeable=False): super().__init__(color) self.name = name self.npc_dir = 1 # NPC initially looks downward self.npc_type = 0 self.env = env self.knowledgeable = knowledgeable self.npc_actions = [] self.dancing_step_idx = 0 self.actions = MiniGridEnv.Actions self.add_npc_direction = True self.available_moves = [self.rotate_left, self.rotate_right, self.go_forward, self.toggle_action] self.exited = False def step(self): if self.exited: return if all(np.array(self.cur_pos) == np.array(self.env.door_pos)): # disappear self.env.grid.set(*self.cur_pos, self.env.object) self.cur_pos = np.array([np.nan, np.nan]) # close door self.env.object.toggle(self.env, self.cur_pos) # reset switches door for s in self.env.switches: s.is_on = False # update door self.env.update_door_lock() self.exited = True elif self.knowledgeable: if self.env.object.is_locked: first_wrong_id = np.where(self.env.get_selected_password() != self.env.password)[0][0] print("first_wrong_id:", first_wrong_id) goal_pos = self.env.switches_pos[first_wrong_id] act = self.path_to_toggle_pos(goal_pos) act() else: if all(self.front_pos == self.env.door_pos) and self.env.object.is_open: self.go_forward() else: act = self.path_to_toggle_pos(self.env.door_pos) act() else: self.env._rand_elem(self.available_moves)() self.env.update_door_lock() class SpyingGrammar(object): templates = ["Move your", "Shake your"] things = ["body", "head"] 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 SpyingEnv(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, diminished_reward=True, step_penalty=False, knowledgeable=False, hard_password=False, max_steps=None, n_switches=3 ): assert size >= 5 self.empty_symbol = "NA \n" self.diminished_reward = diminished_reward self.step_penalty = step_penalty self.knowledgeable = knowledgeable self.hard_password = hard_password self.n_switches = n_switches super().__init__( grid_size=size, max_steps=max_steps or 5*size**2, # Set this to True for maximum speed see_through_walls=True, actions=MiniGridEnv.Actions, action_space=spaces.MultiDiscrete([ len(MiniGridEnv.Actions), *SpyingGrammar.grammar_action_space.nvec ]), add_npc_direction=True ) print({ "size": size, "diminished_reward": diminished_reward, "step_penalty": step_penalty, }) def get_selected_password(self): return np.array([int(s.is_on) for s in self.switches]) def _gen_grid(self, width, height): # Create the grid self.grid = Grid(width, height, nb_obj_dims=4) # Randomly vary the room width and height width = self._rand_int(5, width+1) height = self._rand_int(5, height+1) self.wall_x = width - 1 self.wall_y = height - 1 # Generate the surrounding walls self.grid.wall_rect(0, 0, width, height) door_color = self._rand_elem(COLOR_NAMES) wall_for_door = self._rand_int(1, 4) if wall_for_door < 2: w = self._rand_int(1, width-1) h = height-1 if wall_for_door == 0 else 0 else: w = width-1 if wall_for_door == 3 else 0 h = self._rand_int(1, height-1) assert h != height-1 # door mustn't be on the bottom wall self.door_pos = (w, h) self.door = Door(door_color, is_locked=True) self.grid.set(*self.door_pos, self.door) # add the switches self.switches = [] self.switches_pos = [] for i in range(self.n_switches): c = COLOR_NAMES[i] pos = np.array([i+1, height-1]) sw = Switch(c) self.grid.set(*pos, sw) self.switches.append(sw) self.switches_pos.append(pos) # sample password if self.hard_password: self.password = np.array([self._rand_int(0, 2) for _ in range(self.n_switches)]) else: idx = self._rand_int(0, self.n_switches) self.password = np.zeros(self.n_switches) self.password[idx] = 1.0 # Set a randomly coloured Dancer NPC color = self._rand_elem(COLOR_NAMES) self.peer = Peer(color, "Jim", self, knowledgeable=self.knowledgeable) # Place it on the middle left side of the room peer_pos = np.array((self._rand_int(1, width - 1), self._rand_int(1, height - 1))) self.grid.set(*peer_pos, self.peer) self.peer.init_pos = peer_pos self.peer.cur_pos = peer_pos # Randomize the agent's start position and orientation self.place_agent(size=(width, height)) # Generate the mission string self.mission = 'exit the room' # 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 = "" # used for rendering self.conversation = self.utterance def update_door_lock(self): if np.array_equal(self.get_selected_password(), self.password): self.door.is_locked = False else: self.door.is_locked = True self.door.is_open = False def step(self, action): p_action = action[0] utterance_action = action[1:] obs, reward, done, info = super().step(p_action) self.update_door_lock() print("pass:", self.password) if p_action == self.actions.done: done = True self.peer.step() if all(self.agent_pos == self.door_pos): done = True if self.peer.exited: # only give reward of both exited reward = self._reward() # 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) print("conversation:\n", self.conversation) print("utterance_history:\n", self.utterance_history) self.window.set_caption(self.conversation, [self.peer.name]) return obs class Spying8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8) class Spying6x6Env(SpyingEnv): def __init__(self): super().__init__(size=6) # knowledgeable class SpyingKnowledgeableEnv(SpyingEnv): def __init__(self): super().__init__(size=5, knowledgeable=True) class SpyingKnowledgeable6x6Env(SpyingEnv): def __init__(self): super().__init__(size=6, knowledgeable=True) class SpyingKnowledgeable8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True) class SpyingKnowledgeableHardPassword8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, hard_password=True) class Spying508x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, max_steps=50) class SpyingKnowledgeable508x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, max_steps=50) class SpyingKnowledgeableHardPassword508x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, hard_password=True, max_steps=50) class SpyingKnowledgeable1008x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, max_steps=100) class SpyingKnowledgeable100OneSwitch8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, max_steps=100, n_switches=1) class SpyingKnowledgeable50OneSwitch5x5Env(SpyingEnv): def __init__(self): super().__init__(size=5, knowledgeable=True, max_steps=50, n_switches=1) class SpyingKnowledgeable505x5Env(SpyingEnv): def __init__(self): super().__init__(size=5, knowledgeable=True, max_steps=50, n_switches=3) class SpyingKnowledgeable50TwoSwitches8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, max_steps=50, n_switches=2) class SpyingKnowledgeable50TwoSwitchesHard8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, max_steps=50, n_switches=2, hard_password=True) class SpyingKnowledgeable100TwoSwitches8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, max_steps=100, n_switches=2) class SpyingKnowledgeable100TwoSwitchesHard8x8Env(SpyingEnv): def __init__(self): super().__init__(size=8, knowledgeable=True, max_steps=100, n_switches=2, hard_password=True) register( id='MiniGrid-Spying-5x5-v0', entry_point='gym_minigrid.envs:SpyingEnv' ) register( id='MiniGrid-Spying-6x6-v0', entry_point='gym_minigrid.envs:Spying6x6Env' ) register( id='MiniGrid-Spying-8x8-v0', entry_point='gym_minigrid.envs:Spying8x8Env' ) register( id='MiniGrid-SpyingKnowledgeable-5x5-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeableEnv' ) register( id='MiniGrid-SpyingKnowledgeable-6x6-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable6x6Env' ) register( id='MiniGrid-SpyingKnowledgeable-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable8x8Env' ) register( id='MiniGrid-SpyingKnowledgeableHardPassword-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeableHardPassword8x8Env' ) # max len 50 register( id='MiniGrid-Spying50-8x8-v0', entry_point='gym_minigrid.envs:Spying508x8Env' ) register( id='MiniGrid-SpyingKnowledgeable50-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable508x8Env' ) register( id='MiniGrid-SpyingKnowledgeableHardPassword50-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeableHardPassword508x8Env' ) # max len 100 register( id='MiniGrid-SpyingKnowledgeable100-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable1008x8Env' ) # max len OneSwitch register( id='MiniGrid-SpyingKnowledgeable100OneSwitch-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable100OneSwitch8x8Env' ) register( id='MiniGrid-SpyingKnowledgeable50OneSwitch-5x5-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable50OneSwitch5x5Env' ) register( id='MiniGrid-SpyingUnknowledgeable50OneSwitch-5x5-v0', entry_point='gym_minigrid.envs:SpyingUnknowledgeable50OneSwitch5x5Env' ) register( id='MiniGrid-SpyingKnowledgeable50-5x5-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable505x5Env' ) register( id='MiniGrid-SpyingKnowledgeable50TwoSwitches-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable50TwoSwitches8x8Env' ) register( id='MiniGrid-SpyingKnowledgeable50TwoSwitchesHard-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable50TwoSwitchesHard8x8Env' ) register( id='MiniGrid-SpyingKnowledgeable100TwoSwitches-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable100TwoSwitches8x8Env' ) register( id='MiniGrid-SpyingKnowledgeable100TwoSwitchesHard-8x8-v0', entry_point='gym_minigrid.envs:SpyingKnowledgeable100TwoSwitchesHard8x8Env' )