Fast planning through planning graph analysis
Artificial Intelligence
Plan Recognition in Natural Language Dialogue
Plan Recognition in Natural Language Dialogue
Learning domain knowledge for teaching procedural skills
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
COLLAGEN: A Collaboration Manager for Software Interface Agents
User Modeling and User-Adapted Interaction
Learning programs from traces using version space algebra
Proceedings of the 2nd international conference on Knowledge capture
ITSPOKE: an intelligent tutoring spoken dialogue system
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
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Task models are essential components in many approaches to user modelling because they provide the context with which to interpret, predict, and respond to user behavior. The quality of such models is critical to their ability to support these functions. This paper describes work on improving task models that are automatically acquired from demonstration. Modifications to a standard planning algorithm are described and applied to an example learned task model, showing the utility of incorporating plan-based reasoning into task learning systems.