The purpose of this research was to apply machine learning techniques to automate rule generation in the construction of Intelligent Tutoring Systems. By using a pair of intelligent iterative-deepening, depth-first searches, we were able to generate production rules from a set of marked examples and domain background knowledge. Such production rules required independent searches for both the "if" and "then" portion of the rule. This algorithm allows generalized rules with a small number of sub-operations to be generated in a reasonable amount of time, and provides non-programmer domain experts with a tool for developing Intelligent Tutoring Systems.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Nuzzo-Jones, Goss F.

Publisher

• Worcester Polytechnic Institute

Identifier

• 04D022M

Advisor

• Heffernan, Neil

Year

• 2004

Date created

• 2004-01-01

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright