A formal theory of plan recognition and its implementation
Reasoning about plans
A Bayesian model of plan recognition
Artificial Intelligence
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Using plan recognition in human-computer collaboration
UM '99 Proceedings of the seventh international conference on User modeling
Conflict resolution in collaborative planning dialogs
International Journal of Human-Computer Studies - Special issue on collaboration, cooperation and conflict in dialogue systems
Plan Recognition in Natural Language Dialogue
Plan Recognition in Natural Language Dialogue
Bayesian Models for Keyhole Plan Recognition in an Adventure Game
User Modeling and User-Adapted Interaction
Conversation as Action Under Uncertainty
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Scalable and adaptive goal recognition
Scalable and adaptive goal recognition
A collaborative planning model of intentional structure
Computational Linguistics
An architecture for a generic dialogue shell
Natural Language Engineering
Goal recognition through goal graph analysis
Journal of Artificial Intelligence Research
A new model of plan recognition
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Accounting for context in plan recognition, with application to traffic monitoring
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Activity recognition via user-trace segmentation
ACM Transactions on Sensor Networks (TOSN)
A KEYHOLE PLAN RECOGNITION MODEL FOR ALZHEIMER'S PATIENTS: FIRST RESULTS
Applied Artificial Intelligence
Real world activity recognition with multiple goals
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Early Prediction of Student Frustration
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
High-level goal recognition in a wireless LAN
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Probabilistic goal recognition in interactive narrative environments
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Multiple-goal recognition from low-level signals
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
On natural language processing and plan recognition
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Domain Independent Goal Recognition
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
Intention-based decision making with evolution prospection
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
Flexible goal recognition via graph construction and analysis
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Generating artificial corpora for plan recognition
UM'05 Proceedings of the 10th international conference on User Modeling
Intention recognition in the situation calculus and probability theory frameworks
CLIMA'05 Proceedings of the 6th international conference on Computational Logic in Multi-Agent Systems
Modeling sequences of user actions for statistical goal recognition
User Modeling and User-Adapted Interaction
The role of intention recognition in the evolution of cooperative behavior
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Towards a goal recognition model for the organizational memory
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Corpus-based intention recognition in cooperation dilemmas
Artificial Life
State-of-the-art of intention recognition and its use in decision making
AI Communications
Intelligent Decision Technologies
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Goal recognition for dialogue systems needs to be fast, make early predictions, and be portable. We present initial work which shows that using statistical, corpus-based methods to build goal recognizers may be a viable way to meet those needs. Our goal recognizer is trained on data from apian corpus and then used to determine the agent's most likely goal based on that data. The algorithm is linear in the number of goals, and performs very well in terms of accuracy and early prediction. In addition, it is more easily portable to new domains as does not require a hand-crafted plan library.