Regular Article - Statistical and Nonlinear Physics
Stimuli strategy and learning dynamics promote the wisdom of crowds
School of Electronics and Information Engineering, Taizhou University, 318000, Taizhou, Zhejiang, China
2 Academy of Mathematics and Systems Sciences Chinese Academy of Sciences, 100190, Beijing, China
Accepted: 27 November 2021
Published online: 23 December 2021
Collective wisdom is the ability of a group to perform more effectively than any individual alone. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that reinforcement learning stimulus may play the role in enhancing collective voting accuracy. And collective voting bias can be dismissed through self-reinforcing global cooperative learning. Numeric simulations suggest that the provided method can increase collective voting accuracy. We conclude that real-world systems might seek reward-based incentive mechanism as an alternative to surmount group decision error.
© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2021