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Improving User Taught Task Models

  • Phillip Michalak
  • James Allen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4511)

Abstract

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.

Keywords

User Modelling Task Model Planning Domain Intelligent Tutoring System Order Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Phillip Michalak
    • 1
  • James Allen
    • 1
  1. 1.University of Rochester, Rochester, New York 

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