Technical Note: \cal Q-Learning
Machine Learning
Self-organizing maps
Cooperation, dialogue and ethics
International Journal of Human-Computer Studies - Special issue on collaboration, cooperation and conflict in dialogue systems
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Goal formulation based on communicative principles
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Confidence-based adaptivity in response generation for a spoken dialogue system
SIGDIAL '01 Proceedings of the Second SIGdial Workshop on Discourse and Dialogue - Volume 16
Topic identification in natural language dialogues using neural networks
SIGDIAL '02 Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2
Self organization of a massive document collection
IEEE Transactions on Neural Networks
Topic identification in natural language dialogues using neural networks
SIGDIAL '02 Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2
An adaptive plan-based dialogue agent: integrating learning into a BDI architecture
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
An Online Algorithm for Applying Reinforcement Learning to Handle Ambiguity in Spoken Dialogues
TAMC '09 Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation
Usability in location-based services: context and mobile map navigation
UAHCI'07 Proceedings of the 4th international conference on Universal access in human-computer interaction: ambient interaction
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Technological development has made computer interaction more common and also commercially feasible, and the number of interactive systems has grown rapidly. At the same time, the systems should be able to adapt to various situations and various users, so as to provide the most efficient and helpful mode of interaction. The aim of the Interact project is to explore natural human-computer interaction and to develop dialogue models which will allow users to interact with the computer in a natural and robust way. The paper describes the innovative goals of the project and presents ways that the Interact system supports adaptivity on different system design and interaction management levels.