Show Us the Way: Learning to Manage Dialog from Demonstrations

Understand

We present our submission to the End-to-End Multi-Domain Dialog Challenge Track of the Eighth Dialog System Technology Challenge.

• Our proposed dialog system adopts a pipeline architecture, with distinct components for Natural Language Understanding, Dialog State Tracking, Dialog Management and Natural Language Generation.
• At the core of our system is a reinforcement learning algorithm which uses Deep Q-learning from Demonstrations to learn a dialog policy with the help of expert examples.
• We find that demonstrations are essential to training an accurate dialog policy where both state and action spaces are large.