基于Agent的市场空间结构演化

采用基于agent的计算经济学方法对市场空间结构演化进行研究.Agent对以往交易信息的利用方式对市场的空间结构演化过程和分布有重要影响.根据信息共享程度不同考虑了两种极端信息利用方式:公共信息共享,个体信息利用,及在此两种极端情况之间的有限群体信息交流,研究哪种信息共享方式有利于产生中央集中市场,哪种不能.模型中利用了学习、记忆与协作机制.结果表明,在没有中央规划,没有预设任何初始空间结构的情况下,由个体间简单局域相互作用可以产生稳定的全局空间结构.在有公共信息共享或相当程度的信息交流时,市场的空间结构会从分散到集中演化.当个体没有共同的记忆信息,仅靠个体记忆信息,将不能产生集中的市场空间结构.

Evolution of Market Geographic Structure Based on Agent Technology

This paper studies the evolution of geographic market formation. The way agents utilize information from trading history is crucial to the evolution process and the emergence of geographic market structures. Three ways to utilize information are proposed in this paper. Two out of the three are in uttermost conditions namely public information sharing, personal information keeping; and one is in the middle of the former two in the sense of the degree of information sharing, namely information communication within confined groups. Models, with learning, memory, and cooperation mechanisms, are established to study which information sharing mechanism benefits central market formation and which one does not. Results show that stabilized global spatial structure can emerge from simple localized interaction between agents without central planning or any initial biased spatial configuration. When there is public information sharing or when information is well communicated within groups, the geographic market structure will evolve from distributed markets to centralized markets; while when there is just personal information keeping without a common memory, no centralized market emerges.