Variational Auto-Encoder (VAE) (Kingma and Welling, 2013): The structure of the VAE model is similar to that of the Seq2Seq model, except that it has two independent linear layers followed by the encoder to calculate the mean and variance of the distribution of the latent variable separately.
the reward of the agent is: where rw(c, r) is the reward with regard to the conversation c and its reference response r in the dataset.