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Using Rollouts to Induce a Policy from a User Model

  • Joseph E. Beck
  • Beverly Park Woolf
Conference paper
  • 678 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2109)

Abstract

This research describes the application of an executable user model to generate policies to adapt software to best fit the user. Our approach first gathers data describing how users behave, and uses these data to induce a computational model that predicts how users will perform in a particular situation. Since system designers have differing goals, our architecture takes an arbitrary goal that the designer would like to see users achieve. Our architecture than using rollout techniques to determine how software should act in a particular situation with the user in order to achieve the desired goal.

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References

  1. 1.
    Joseph E. Beck and Beverly P. Woolf. Learning to teach: A machine learning architecture for making teaching decisions. In Proceedings of the Seventeenth National Conference on Artificial Intelligence, 2000.Google Scholar
  2. 2.
    Dimitri P. Bertsekas and John N. Tsitsiklis. Neuro-Dynamic Programming. Athena Scientific, Belmont, Massachusetts; U.S.A., 1996.zbMATHGoogle Scholar
  3. 3.
    H. Nwana and P. Coxhead. Towards an intelligent tutoring system for fractions. In Proceedings of First International Conference on Intelligent Tutoring Systems, pages 403–408, 1988.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Joseph E. Beck
    • 1
  • Beverly Park Woolf
    • 1
  1. 1.Computer Science DepartmentUniversity of MassachusettsAmherstUSA

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