Here we employ the Deep Qnetwork (DQN) (Mnih et al., 2015).
at each step, the agent observes the dialogue state s, then chooses an action a using an -greedy policy that selects a random action with probability , and otherwise follows the greedy policy a = arg max a Q(s, a ; θ Q ).