Paper: Automatic Optimization Of Dialogue Management

ACL ID C00-1073
Title Automatic Optimization Of Dialogue Management
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2000

Designing the dialogue strategy of a spoken dialogue system involves many nontrivial choices. This pa- per I)resents a reinforcement learning approach for automatically optimizing a dialogue strategy that addresses the technical challenges in applying re- inforcement learning to a working dialogue system with hulnan users. ¥e then show that our approach measurably improves performance in an experimen- tal system.