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智能体和元胞自动机是基于复杂适应系统理论(CAS)框架下应用较成熟的两种行为模拟方法,在对它们的优缺点及适用领域进行比较分析的基础上,构建了一种更适合人类复杂行为模拟的新方法——“CA结构的智能Agent”.并将其应用于股市投资者行为的模拟研究中,模拟结果验证了股市投资行为中的羊群行为和复杂系统特性.此外,模拟还发现股市达到均衡的时间和状态取决于投资者的类型和比例.
Based on the complex adaptive system theory (CAS) framework, the agent and cellular automata are two more mature methods of behavior simulation. Based on the comparative analysis of their advantages and disadvantages and applicable fields, a more suitable A new method of simulating human complex behavior - “Intelligent Agent of CA Structure” is applied in the simulation study of the stock market investor behavior. The simulation results verify herding behavior and complex system characteristics in the stock market investment behavior. In addition, the simulation also found that the time and the state of the stock market to reach equilibrium depends on the type and proportion of investors.