Agenda-Based User Simulation for Bootstrapping a POMDP Dialogue System

This paper investigates the problem of bootstrapping a statistical dialogue manager without access to training data and proposes a new probabilistic agenda-based method for simulating user behaviour. In experiments with a statistical POMDP dialogue system, the simulator was realistic enough to successfully test the prototype system and train a dialogue policy. An extensive study with human subjects showed that the learned policy was highly competitive, with task completion rates above 90%.

• Type: Conference
• Year: 2007
• Where: NAACL
• Authors: Jost Schatzmann, Blaise Thomson, Karl Weilhammer, Hui Ye, Steve Young
• Keywords: Computational Linguistics, Dialogue Policy, NAACL 2007, Statistical Dialogue Manager, Statistical Pomdp Dialogue