It computes the probability D (y|x, {c}) that the response is humangenerated given an input message x and N-best response candidates {c} = {c 1 , ...c k , ..., c N }, where denote the parameters of the discriminator.
its objective function is to minimize classification error rate: We cast the retrieval-enhanced response generation as a reinforcement learning problem to backpropagate the error computed by the discriminator to the generator via the policy gradient algorithm.