Bayesian Solution to the 20 Question Game with Application to Recommender Systems
Title: A Bayesian Strategy to the 20 Question Game with Applications to Recommender Systems Author: Sunith R. Suresh Advisor: David L. Banks Abstract: In this paper, we develop an algorithm that utilizes a Bayesian strategy to determine a sequence of questions to play the 20 Question game. The algorithm is motivated with an application to active recommender systems. We first develop an algorithm that constructs a sequence of questions where each question inquires only about a single binary feature. We test the performance of the algorithm utilizing simulation studies, and find that it performs relatively well under an informed prior. We modify the algorithm to construct a sequence of questions where each question inquires about 2 binary features with AND conjunction. We test the performance of the modified algorithm via simulation studies, and find that it does not significantly improve performance.