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A Space-Efficient Technique of Policy Trees for an Intelligent Tutoring System on POMDP

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Computer Supported Education (CSEDU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1022))

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Abstract

Adaptive tutoring is essentially a decision process, in each step of which an optimal tutoring action is chosen and taken. In recent years, researchers have been increasingly interested in applying the partially observable Markov decision process (POMDP) model to build intelligent tutoring systems (ITSs). The POMDP model may enable an ITS to optimize tutoring when uncertainties exist. Computing in a POMDP is characterized by exponential costs, in both time and space, which obstruct the POMDP model for practical applications. In our research, we develop techniques to improve computing efficiency in a POMDP based ITS. In this paper, we report a space-efficient technique of policy trees. The technique may help achieve high space efficiency by grouping policy trees and dynamically creating the policy trees to be evaluated in making a decision.

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Acknowledgements

This research is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Authors and Affiliations

  1. University of Guelph, Guelph, ON, N1G 2W1, Canada

    Fangju Wang

Authors
  1. Fangju Wang
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Correspondence to Fangju Wang .

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Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Bruce M. McLaren

  2. MIT, Cambridge, MA, USA

    Rob Reilly

  3. University of Denver, Denver, CO, USA

    Susan Zvacek

  4. University of Ulster, Newtownabbey, UK

    James Uhomoibhi

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Wang, F. (2019). A Space-Efficient Technique of Policy Trees for an Intelligent Tutoring System on POMDP. In: McLaren, B., Reilly, R., Zvacek, S., Uhomoibhi, J. (eds) Computer Supported Education. CSEDU 2018. Communications in Computer and Information Science, vol 1022. Springer, Cham. https://doi.org/10.1007/978-3-030-21151-6_13

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  • DOI: https://doi.org/10.1007/978-3-030-21151-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21150-9

  • Online ISBN: 978-3-030-21151-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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