Optimizing Information Sharing in Crowd Networks based on Reinforcement Learning

Abstract

With the progress of human society and the development of machine learning technology in recent years, crowd intelligence has become more and more widespread. Specifically, to optimize the finishing quality of complicated tasks, various homogeneous and heterogeneous intelligent agents (including both human and machines) are interconnected to form more and more complex and diverse intelligent networks named crowd networks, where agents can interact and collaborate with each other. In the process of