AI seminar: A mixed-initiative intelligent tutoring system for sudoku

Speaker: Allan Caine

In this talk, we propose a model called MITS --- Mixed Initiative Intelligent Tutoring System for Sudoku. Extrapolating from theory for tutoring in scholastic subjects, and tutoring in the game of chess, we develop a model for tutoring the game of Sudoku using a mixed-initiative paradigm. Moreover, our aim is to design a system which not only proposes moves to make but also gives advice on why a particular move ought to be made. We operate in a decision-theoretic framework that measures the benefits and costs of interacting with students who are learning the game. The tutor will take the initiative to interact when the student lacks knowledge and is making moves that have low utility. But it will also interact when the student takes the initiative to elicit further input on the game he or she is trying to play. We illustrate our graphic user interface prototype and take the reader through a sample session. As a result, we present a system that is useful not only to gain insight into how to tutor students about strategy games but also about how to support mixed-initiative interaction in tutorial settings.