Attention, intentions, and the structure of discourse
Computational Linguistics
An Overview of MAXQ Hierarchical Reinforcement Learning
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
Human-Robot dialogue for joint construction tasks
Proceedings of the 8th international conference on Multimodal interfaces
Evaluation of a hierarchical reinforcement learning spoken dialogue system
Computer Speech and Language
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We demonstrate a conversational humanoid robot that allows users to follow their own dialogue structures. Our system uses a hierarchy of reinforcement learning dialogue agents, which support transitions across sub-dialogues in order to relax the strictness of hierarchical control and therefore support flexible interactions. We demonstrate our system with the Nao robot playing two versions of a Quiz game. Whilst language input and dialogue control is autonomous or wizarded, language output is provided by the robot combining verbal and non-verbal contributions. The novel features in our system are (a) the flexibility given to users to navigate flexibly in the interaction; and (b) a framework for investigating adaptive and flexible dialogues.