Improving the Accuracy of the Collective Prediction by Maintaining the Diversity of Opinions: Preliminary Report

抄録

This study aims to improve prediction accuracy by fostering diversity of opinions. We take an approach to give incentive to agents and induce diverse opinions and focus the minority reward system. The previous study assumes that the number of agents is sufficiently large, but the number of agents may be small in real-world situations. We show that the minority reward system is not necessarily efficient if the number of agents is small such as 100. To overcome this drawback, we propose a method to improve the performance by tuning the threshold for determining the minority and show the preliminary result of the evaluation.