Title

A category-based self-improving planning module

Authors

Roberta Legaspi

College

College of Computer Studies

Document Type

Article

Source Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

3220

First Page

554

Last Page

563

Publication Date

1-1-2004

Abstract

Though various approaches have been used to tackle the task of instructional planning, the compelling need is for ITSs to improve their own plans dynamically. We have developed a Category-based Self-improving Planning Module (CSPM) for a tutor agent that utilizes the knowledge learned from automatically derived student categories to support efficient on-line selfimprovement. We have tested and validated the learning capability of CSPM to alter its planning knowledge towards achieving effective plans for various student categories using recorded teaching scenarios. © Springer-Verlag 2004 References.

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Digitial Object Identifier (DOI)

10.1007/978-3-540-30139-4_52

Disciplines

Computer Sciences | Educational Technology

Keywords

Computer-assisted instruction; Intelligent tutoring systems

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