复杂系统与国际关系研究

【作者】 刘慧；

【导师】 秦亚青；

【作者基本信息】 外交学院 ， 国际关系， 2008， 博士

【摘要】 本文写作的目的主要在于综述复杂系统在国际关系中的研究应用,具体包括研究对象、科学哲学、研究方法、主要研究成果等。复杂性科学基础上复杂系统研究以“非线性、自组织、涌现模式”代替了传统研究中的“稳定、均衡、线性的模式”,开拓了国际关系研究的新领域。复杂系统对国际关系研究的影响体现在一下几个方面:第一,研究对象从简单系统转向复杂系统。不同于简单系统对稳定性规则的寻求,复杂系统强调系统内在要素之间的相互关系。第二,科学哲学基础从实证主义、后实证主义转向演化实在论。演化实在论综合了科学实在论和语义分析的模型方法,认为理论只解释模型行为,它的检验是在模型所塑造的隔离的理想世界中进行的。语义观念降低了公理的重要性,强调模型作为一个自主个体对科学的发展具有重要影响。第三,形式模型从理性选择模型转向基于个体模型(ABM)。ABM作为一种动态化的形式模型,不再需要个体同质性和平衡条件的数学假定,能够用来表示微观机制产生宏观结构的过程。国际关系领域的复杂性研究以罗伯特·阿克塞尔罗德(Robert Axelrod)、托马斯·谢林(Thomas C. Shelling)、拉斯-埃里克·锡德曼(Lars-Erik Cederman)、罗伯特·杰维斯(Robert Jervis)、詹姆士·罗西瑙(James N. Rosenau)、玛蒂尔达·阿尔伯特(Mathias Albert)等学者为代表,他们的研究可以分为三类:第一,隐喻分析。罗西瑙的湍流范式,杰维斯的复杂系统效应,阿尔伯特的世界社会观借用了复杂系统思想来分析国际政治。第二,基于个体模型。基于个体模型是复杂性科学研究的主要方法,谢林、阿克塞尔罗德的研究被视为基于个体建模的早期代表。一些学者还将复杂性建模用于对民主和平论的研究。此外,复杂性建模与建构主义思想有着广泛的结合空间。第三,批判研究。复杂性科学与后现代主义都认为,不能以单一的、排他的叙述来分析复杂现象。然而,后现代主义从发现真理转移到相对主义的叙事建构,复杂性科学坚持对外部事实的指涉,坚持有效的科学研究。国际关系研究的科学历程开始于卡尔的现实主义转向,经由行为主义的量化分析再到后实证主义的反科学立场,科学在这一进程中的地位极为尴尬,问题症结在于经典科学的封闭、机械、线性观,复杂性科学试图克服经典科学的局限性,并继续进行有效的科学研究。复杂性研究不那么关注各种“主义”,而是注重分析和解决一个细小的问题。然而,复杂系统研究并不是一种实质性理论,而主要是作为研究工具被发展的,它体现了学科的研究前沿,开创了国际关系研究的新路径。同时,社会系统具有权威结构,这和没有中央权威的复杂系统是根本不同的,因而以复杂系统类比具有等级制特征的社会系统是不恰当的。此外,复杂系统研究本身并不能证实或证伪某一假设,因而只是一种思想试验。简言之,它是一种关于过程的理论,而不是一种政治理论。因此,为理解全球政治的复杂现实,研究者除了借助于复杂适应系统建模外,还需要经验研究,这说明传统的研究方法(如个案研究、统计模型等)仍然是必不可少的。更多还原

【Abstract】 The dissertation intends to review the application of complex system in international relations studies, including research subject, science philosophy, method, and relevant works. Complex system research replaces the stability and linear model with nonlinear and emergent model. It also encourages innovative methods for understanding political reality and offers a novel perspective on world politics: Firstly, research subject transfers from simple system to complex system. Different from stability oriented simple system, complex systems are always dynamic and emphasize the relationships between factors in the system. Secondly, science philosophy changes from positivism, post-positivism to evolutionary realism. Since the death of positivism in the 1970s, philosophers have turned to scientific realism, evolutionary epistemology, and the semantic conception of theories. Building on these trends, complexity science offers a new normal science epistemology—evolutionary realism. It combines scientific realism with semantic relativism, focusing on order creation by self-organizing heterogeneous agents and agent-based model, not requiring the mathematical assumptions of agent homogeneity and equilibrium conditions. In the Semantic Conception, the quality of a science is measured by how well it explains the dynamics of phase-spaces—not by reduction back to axioms. Thirdly, formal model transfers from rational choice model to agent-based model. As a kind of dynamic formal model, the unifying goal of this method is to simulate and understand processes through which macro or social patterns emerge from the actions and interactions of agents (and their context), and in many applications agents are heterogeneous and adaptive, rather than homogeneous and rational.Scholars of international politics have embraced the idea of complexity and methods of complex system theory, and yet have little agreement over the role of complex systems in our thinking about global politics. Their researches can be classified into three kinds: Firstly, as a metaphor or heuristic, turbulence paradigm, complex system effect and world society borrows some ideas from complexity system theory to analyze international politics. Secondly, as a method, Thomas C. Shelling and Robert Axelrod are considered as the pioneers of complex-systems modeling. Some researchers applied this method in democratic peace studies. Moreover, viewed as a complement to qualitative theoretical and historical work, complexity modeling are useful in assisting the scholar in disentangling thorny conceptual puzzles and in keeping track of involved spatiotemporal processes, as advocated by constructivist scholars; thirdly, as a tool of critical inquiry, Paul Cilliers explores the notion of complexity in light of contemporary perspectives from philosophy and science, and reinterpret postmodern theory in order to argue that a postmodern perspective does not necessarily imply relativism. Complexity science sets the limit for research, which orients toward objective and scientific research rather than philosophical and purely narrative construction.The scientific studies of international relations were initiated by Edward H. Carr switching to realism, followed first by the quantitative analysis of behaviorism and then by the anti-scientific stance of post positivism. Science in this process was left in an embarrassing position due to conventional science being static, mechanistic and linear. Complexity science intends to move beyond the orthodoxy of conventional science and continue effective scientific research. Researchers of complex system have largely eschewed the grand theoretical debates between various‘isms’. In other words, complex system is not a substantive theory of international relations (or anything else, for that matter). It is an analytical tool with which the implications of particular substantive assumptions about the real world can be hammered out. Despite these advantages, scholars of international politics remain skeptical about complex system’s method. While complexity is a meaningful metaphor, complex systems differ in important ways from social and political systems. Although they may behave in complicated and confusing ways, political systems have structures of authority that may be inconsistent with the definition of complex system. Moreover, the methods of complex systems theory alone cannot prove or disprove hypotheses about global politics—although it is a theory of process, it cannot be a theory of politics. To make sense of the intricacies of global politics, then, researches who use simulations of complex systems must supplement these efforts with empirical investigations.更多还原