Modeling of Agent-Based Complex Network to Detect the Trust of Investors in P2P Platform

Abstract

Due to the lopsided nature of investor investment-related model research under the traditional P2P environment, and in order to improve the research effect, this study proposes an agent-based complex network testing investor trust model. This model is based on interest trust, and combines with the Bayesian method to effectively evaluate the model trust, and builds a multi-steady-state agent system based on this. At the same time, it effectively analyzes the evolutionary mechanism of the system, and validates the model's application in combination with comparative experiments. The research shows that the model can effectively improve the success rate of executing tasks and shorten the distance between cooperative agents, thus ensuring the reliability of the selection of cooperative objects and providing theoretical reference for subsequent related research.