Introducing Uninformed Search with Tangible Board Games

Abstract

Researchers have established the value of hands-on learning with tangible artifacts in mathematics and related fields. Inspired by this work, an assignment was developed for an undergraduate/graduate Artificial Intelligence course to introduce students to the formal representation of search. Students analyzed a familiar board game — e.g., Rush Hour or peg solitaire — using the standard approach to modeling an uninformed search process. The assignment was well-received by students, and analysis of their work yielded unexpected insights into the challenges students face in understanding how the formal problem model interacts with search algorithms. This paper introduces the theoretical motivations for the work, analyzes student work products, and makes recommendations for future extensions.