JSAI2019

JSAI2019

Jun 4 - Jun 7, 2019TOKI MESSE, Niigata Convention Center
The Japanese Society for Artificial Intelligence
JSAI2019

JSAI2019

Jun 4 - Jun 7, 2019TOKI MESSE, Niigata Convention Center

[2O5-E-3-01]Improving the Accuracy of the Collective Prediction by Maintaining the Diversity of Opinions: Preliminary Report

〇Rui Chen1, Shigeo Matsubara1(1. Kyoto University)

Keywords:

Collective intelligence,Incentive

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.