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PLURALISTIC MODELING OF COMPLEX SYSTEMS

机译：复杂系统的公共模型

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The modeling of complex systems such as ecological or socio-economic systems can be very challenging. Although various modeling approaches exist, they are generally not compatible and mutually consistent, and empirical data often do not allow one to decide what model is the right one, the best one, or most appropriate one. Moreover, as the recent financial and economic crisis shows, relying on a single, idealized model can be very costly. This contribution tries to shed new light on problems that arise when complex systems are modeled. While the arguments can be transferred to many different systems, the related scientific challenges are illustrated for social, economic, and traffic systems. The contribution discusses issues that are sometimes overlooked and tries to overcome some frequent misunderstandings and controversies of the past. At the same time, it is highlighted how some long-standing scientific puzzles may be solved by considering non-linear models of heterogeneous agents with spatio-temporal interactions. As a result of the analysis, it is concluded that a paradigm shift towards a pluralistic or possibilistic modeling approach, which integrates multiple world views, is overdue. In this connection, it is argued that it can be useful to combine many different approaches to obtain a good picture of reality, even though they may be inconsistent. Finally, it is identified what would be profitable areas of collaboration between the socio-economic, natural, and engineering sciences.
机译：诸如生态或社会经济系统之类的复杂系统的建模可能非常具有挑战性。尽管存在各种建模方法，但它们通常不兼容且相互一致，并且经验数据通常不允许人们决定哪种模型是正确的模型，最佳模型或最合适的模型。而且，正如最近的金融和经济危机所显示的那样，依靠一个单一的，理想化的模型可能会非常昂贵。这种贡献试图为建模复杂系统时出现的问题提供新的思路。尽管论点可以转移到许多不同的系统，但对于社会，经济和交通系统却说明了相关的科学挑战。该文稿讨论了有时被忽略的问题，并试图克服过去的一些常见误解和争议。同时，强调了如何通过考虑具有时空相互作用的异质主体的非线性模型来解决一些长期存在的科学难题。分析的结果表明，向多元或可能性建模方法转变的范式已经过时了，该方法整合了多种世界观。在这方面，有人认为，将许多不同的方法结合起来以获得对现实的良好印象可能是有用的，即使它们可能不一致。最后，确定了社会经济，自然科学和工程科学之间合作的有利领域。

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  • 来源
    《Science and Culture》 |2010年第10期|p.315-329|共15页
  • 作者

    DIRK HELBING;

  • 作者单位

    ETH Zurich, CLU, Clausiusstr. 50, 8092 Zurich, Switzerland ,Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501,USA;

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