Dynamical Creation of Policy Trees for a POMDP-based Intelligent Tutoring System

Fangju Wang

2018

Abstract

In this paper, we discuss a new technique for creating policy trees in an intelligent tutoring system (ITS) that is based on a partially observable Markov decision process (POMDP). The POMDP model is a useful tool for dealing with uncertainties. With a POMDP, an ITS may choose optimal teaching actions even when uncertainties exist. Great computational complexity in solving a POMDP has been a major obstacle to applying the POMDP model to intelligent tutoring. The technique of policy trees is considered a less expensive approach. However, policy trees are still too expensive for building ITSs that teach practical subjects. In our research, we develop a new technique of policy trees, in which trees are grouped and dynamically created. This technique has advantages of better time and space efficiencies. It enables us to build more efficient ITSs. Particularly the technique makes it possible to build ITSs on platforms which have limited storage capacity and computing power.

Paper Citation

in Harvard Style

Wang F. (2018). Dynamical Creation of Policy Trees for a POMDP-based Intelligent Tutoring System.In Proceedings of the 10th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-291-2, pages 137-144. DOI: 10.5220/0006774601370144

in Bibtex Style

@conference{csedu18,
author={Fangju Wang},
title={Dynamical Creation of Policy Trees for a POMDP-based Intelligent Tutoring System},
booktitle={Proceedings of the 10th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2018},
pages={137-144},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006774601370144},
isbn={978-989-758-291-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Dynamical Creation of Policy Trees for a POMDP-based Intelligent Tutoring System
SN - 978-989-758-291-2
AU - Wang F.
PY - 2018
SP - 137
EP - 144
DO - 10.5220/0006774601370144