Learning to Compose Effective Strategies from a Library of Dialogue Components
Martijn Spitters, Marco De Boni, Jakub Zavrel, Remko Bonnema · 2007
This paper describes a method for automatically learning effective dialogue strategies, generated from a library of dialogue content, using reinforcement learning from user feedback. This library includes greetings, social dialogue, chit-chat, jokes and relationship building, as well as the more usual clarification and verification components of dialogue. We tested the method through a motivational dialogue system that encourages take-up of exercise and show that it can be used to construct good dialogue strategies with little effort. 1