复杂性科学理论与区域空间演化模拟研究  

Sciences of complexity and studies of evolutional simulation of regional spatial structure

作　　者：薛领[1] 杨开忠[1] 

机构地区：[1]北京大学城市与环境学系,北京100871

出　　处：《地理研究》2002年第1期79-88,共10页Geographical Research

基　　金：国家自然科学基金资助项目区域复杂空间格局演化规律的研究 (4 99710 2 7)

摘　　要：针对传统上两类模拟区域空间演化的模型策略 ,着重讨论了它们的建模思想和手段 ,在此基础上介绍了复杂性 (Complexity)研究的重要成果———复杂适应系统 (CAS)理论的基本概念以及CAS模型的思想 ,探讨了区域作为复杂适应系统的一般特征 。During the last two decades, a lot of innovations have appeared in the field of urban and regional research. New paradigms and approaches such as dynamics of complex systems, self-organization, evolution theory, have been recognized for better understanding the evolutional process of regional spatial structure. It can be seen as a cumulative and aggregated order which results from numerous locally made decisions. Therefore the basic force driving the evolution of regional system is inherently microscopic. Regional system is an evolving complex system which grows from simple to intricacy. Inspired by the concept of biology, regional system also evolves into a complex, multiplex and vitality state by certain natural selection and adaptation. The understanding that the region is a complex adaptive system (CAS) means that microscopic simulation emphasizing the way in which locally made decisions and interaction between all kinds of local agents such as households and enterprises give rise to global patterns is highly appropriate. The methodology of CAS model is a part of theory of CAS. The CAS such as urban and regional system is conceived as societies of autonomous agents who are able to act both on themselves and on their environments. The general behavior of the regional spatial evolution is produced by the combination of actions of the households and enterprises. The determinants of an agent's behavior have a local character and there is no global constraint on the system's evolution. These agents can adapt to other agents and environment continuously by learning from their own experience. The classifier system is a good learning algorithm for representation of the agent's adaptation. Therefore, it is a good alternative way of simulating the evolutional process of the regional spatial structure by modeling behaviors of these local active agents and their interactions. It is easy to build and understand the CAS model. The CAS model can overcome the limit of perfect rationality by introducing learning algorithm an

关 键 词：区域 CAS 主体 模型 模拟 复杂性科学理论 城市 空间演化 模拟 

分 类 号：N94[自然科学总论—系统科学]