def __init__(self, configuration):
super().__init__()
# There is only one agent in this setting
self.agent_id = 0
# Dialogue statistics
self.dialogue_episode = 0
self.dialogue_turn = 0
self.num_successful_dialogues = 0
self.num_task_success = 0
self.cumulative_rewards = 0
self.total_dialogue_turns = 0
self.minibatch_length = 50
self.train_interval = 10
self.num_batches_per_epoch = 10
self.SAVE_LOG = True
# The dialogue will terminate after MAX_TURNS (this agent will issue
# a bye() dialogue act.
self.MAX_TURNS = 15
self.dialogue_turn = -1
self.dialogue_manager = None
self.user_model = None
self.agent_goal = None
self.goal_generator = None
self.prev_turnstate = TurnState()
self.curr_state = None
self.recorder = DialogueEpisodeRecorder()
# TODO: Handle this properly - get reward function type from config
self.reward_func = SlotFillingReward()
self.ontology, self.database = build_domain_settings(
configuration["DIALOGUE"])
self.user_simulator = AgendaBasedUS(
goal_generator=Goal.GoalGenerator(self.ontology, self.database),
error_model=ErrorModel(
self.ontology,
slot_confuse_prob=0.0,
op_confuse_prob=0.0,
value_confuse_prob=0.0,
),
)
self.dialogue_manager = DialogueManager.DialogueManager(
configuration,
self.ontology,
self.database,
self.agent_id,
"system",
configuration["AGENT_0"]["DM"]["policy"],
)
