Neural Policy Network: For the neural approach, similar to (Williams and Zweig, 2016; Zhao and Eskenazi, 2016), we use an RNN to allow the network to maintain an internal state of dialogue history.
we use a GRU unit followed by a fully-connected layer and softmax nonlinearity to model the policy π over actions in During training, the agent samples its actions from the policy to encourage exploration.