Multi-Agent Simulation Model of China's Real Estate Market Based on Bayesian Network Decision Making

In recent years, agent-based modeling and simulation (ABMS) methods have attracted the people's attention in the field of management science and is becoming a important tool for solving complex problems. In this paper, the Bayesian network is introduced to ABMS methods, and a multi-agent system of China's real estate market is proposed based on the Bayesian network with uncertain information, which has the abilities of online learning and effect describing for group behavior. China's real estate market ecology is simulated by the system. Simulation results can accurately reproduce the operation of China's real estate market, so to prove the effectiveness of the model. Through simulating for related parameters, some valuable findings on operation rule of estate market are obtained. The model and method developed in the paper provide reference for studying China's real estate market rules.