Single-model multi-domain dialogue management with deep learning

Abstract

We present a Deep Learning approach to dialogue management for multiple domains. Instead of training multiple models (e.g. one for each domain), we train a single domain-independent policy network that is applicable to virtually any information-seeking domain. We use the Deep Q-Network algorithm to train our dialogue policy, and evaluate against simulated and paid human users. The results show that our algorithm outperforms previous approaches while being more practical and scalable.