Bayesian and belief-functions formalisms for evidential reasoning: a conceptual analysis
Readings in uncertain reasoning
Discourse structure in the TRAINS project
HLT '91 Proceedings of the workshop on Speech and Natural Language
A plan-based model for response generation in collaborative task-oriented dialogues
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Spoken natural language dialog systems: a practical approach
Spoken natural language dialog systems: a practical approach
Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
The Trains 91 Dialogues
The TRAINS 93 Dialogues
Control of mixed-initiative discourse through meta-locutionary acts: a computational model
Control of mixed-initiative discourse through meta-locutionary acts: a computational model
Tracking initiative in collaborative dialogue interactions
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Toward a plan-based understanding model for mixed-initiative dialogues
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
A three-level model for plan exploration
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
A tripartite plan-based model of dialogue
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Response generation in collaborative negotiation
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Mixed initiative in dialogue: an investigation into discourse segmentation
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Mechanisms for mixed-initiative human-computer collaborative discourse
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Cues and control in expert-client dialogues
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
Redundancy in collaborative dialogue
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 1
Artificial Intelligence Review
An Evidential Model for Tracking Initiative in Collaborative Dialogue Interactions
User Modeling and User-Adapted Interaction
Acknowledgments in human-computer interaction
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Tracking initiative in collaborative dialogue interactions
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Exploring the characteristics of multi-party dialogues
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
The CommandTalk spoken dialogue system
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Reconciling initiative and discourse structure
SIGDIAL '01 Proceedings of the Second SIGdial Workshop on Discourse and Dialogue - Volume 16
So Let's See: Taking and Keeping the Initiative in Collaborative Dialogues
IVA '07 Proceedings of the 7th international conference on Intelligent Virtual Agents
Journal of Artificial Intelligence Research
Optimizing dialogue management with reinforcement learning: experiments with the NJFun system
Journal of Artificial Intelligence Research
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In this paper, we argue for the need to distinguish between task and dialogue initiatives, and present a model for tracking shifts in both types of initiatives in dialogue interactions. Our model predicts the initiative holders in the next dialogue turn based on the current initiative holders and the effect that observed cues have on changing them. Our evaluation across various corpora shows that the use of cues consistently improves the accuracy in the system's prediction of task and dialogue initiative holders by 2-4 and 8-13 percentage points, respectively, thus illustrating the generality of our model.