收稿日期: 2002-12-23
修回日期: 2003-05-09
网络出版日期: 2004-04-01
基金资助
国家自然科学基金项目“区域复杂空间格局演化规律的研究”（编号：49971027）资助
AGENTBASED MODELING: THE NEW ADVANCE IN GEOCOMPUTATION
Received date: 2002-12-23
Revised date: 2003-05-09
Online published: 2004-04-01
20世纪90年代后期，基于agent建模（AgentBasedModeling，ABM）的理论和技术不断发展，并且逐渐引起地理研究者的重视。ABM这种自下而上的模型策略是复杂适应系统理论、人工生命以及分布式人工智能技术的融合，目前已经成为继面向对象方法之后出现的又一种进行复杂系统分析与模拟的重要手段。ABM关注的是地理系统中大量异质性个体间的相互关系，强调进化和适应行为，主张非均衡的发展路径，我们必须为个别的决策者建立微观行为模型，并且通过观察大量的微观a gent的相互作用来研究宏观上整个地理系统的空间演化过程。将在简要回顾地理空间演化模型的基础上重点讨论ABM出现的理论背景、技术优势、研究进展以及模拟系统的开发问题。
关键词： 地理计算; 模拟; 城市和区域; 基于agent的建模
杨开忠 , 沈体雁 , 薛领 . 基于agent的建模———地理计算的新发展[J]. 地球科学进展, 2004 , 19(2) : 305 -311 . DOI: 10.11867/j.issn.1001-8166.2004.02.0305
Agent-based modeling (ABM) is currently a new active research area in Geocomputation. The methodology of ABM is integration of the theories and technologies of complex adaptive system, artificial life and distributed artificial intelligence. The complex system such as geographical system is conceived as societies of autonomous agents that are able to act both on themselves and on their environments. The agents can communicate and interact with other agents. The determinants of an agent's behavior have a local character and there is no global constraint on the system's evolution. Therefore, it is a good alternative way of simulating the evolutional process of the spatial structure by modeling behaviors of these local active agents and their interactions. Such a multi-agent model allows a greater variety of spatial interaction, including variable extension of the spatial range of interactions, which can be defined by the connectivity of a network according to the characteristics of each agent. Moreover, instead of allowing only a few quantitative variables in non-linear equation and possible states for each cells in cellular automata, the ABM is able to integrate any qualitative or quantitative description of an agent, whose behavior may be very complicated. The flexible modeling method allows for a much more detailed representation of spatial interactions and of some local properties and also makes it possible to introduce new agents or new rules in the model without changing the other parts. This paper gives an overview on the theory background and technology advantages of ABM compared with Equation-based Modeling(EBM) and Cellular Automata(CA). Since interaction and adaptation between agents is the central task of ABM, this article gives a detail discussion on the structure, characteristics and internal mechanisms of an agent. Its related problems such as research advance and the platform of ABM are also surveyed.
Key words： Agent-based modeling; Geocomputation; Simulation; City and region.
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