复杂适应系统

A complex adaptive system is a system in which a perfect understanding of the individual parts does not automatically convey a perfect understanding of the whole system's behavior.^[1] In complex adaptive systems, the whole is more complex than its parts,^[2] and more complicated and meaningful than the aggregate of its parts. The study of complex adaptive systems, a subset of nonlinear dynamical systems,^[3] is highly interdisciplinary and blends insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior.^[4]

A complex adaptive system is a system in which a perfect understanding of the individual parts does not automatically convey a perfect understanding of the whole system's behavior. In complex adaptive systems, the whole is more complex than its parts, and more complicated and meaningful than the aggregate of its parts. The study of complex adaptive systems, a subset of nonlinear dynamical systems, is highly interdisciplinary and blends insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior.

复杂适应性系统(Complex adaptive system)是一种系统，在这种系统中，对系统部分行为的理解并不能完美解释系统的整体行为^[1]。在复杂适应系统中，系统的整体比其单独某个组成部分^[5]或部分的加和都更加复杂、更有意义。复杂适应系统是非线性动力系统的子集^[3]，其研究是高度跨学科的，融合了自然科学和社会科学的知识开发出了系统级的模型和见解，从而使得系统可以实现异构代理（Heterogeneous agents）、相变（Phase transition）和涌现行为（Emergent behavior）^[6] 。

They are complex in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities, i.e., the behavior of the ensemble is not predicted by the behavior of the components. They are adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events.^[7]^[8]^[1] They are a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure.^[7]^[8]^[9] The Complex Adaptive Systems approach builds on replicator dynamics.^[10]

They are complex in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities, i.e., the behavior of the ensemble is not predicted by the behavior of the components. They are adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events.

这种系统是复杂系统/复杂的，因为它们是动态的交互网络(Dynamic network analysis)，并不是单个静态实体的简单聚合，也就是说，集合的行为不能通过每个组件的行为来进行预测。同时它们也是适应性的，因为个体和集体的行为会随着微事件或事件集合的发生而进行变异或自我组织。

概述 Overview

The term complex adaptive systems, or complexity science, is often used to describe the loosely organized academic field that has grown up around the study of such systems. Complexity science is not a single theory—it encompasses more than one theoretical framework and is highly interdisciplinary, seeking the answers to some fundamental questions about living, adaptable, changeable systems. Complex adaptive systems may adopt hard or softer approaches ^[11]. Hard theories use formal language that is precise, tend to see agents as having tangible properties, and usually see objects in a behavioral system that can be manipulated in some way. Softer theories use natural language and narratives that may be imprecise, and agents are subjects having both tangible and intangible properties. Examples of hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and a class of softer theory is Viable System Theory. Many of the propositional consideration made in hard theory are also of relevance to softer theory. From here on, interest will now center on CAS.

The term complex adaptive systems, or complexity science, is often used to describe the loosely organized academic field that has grown up around the study of such systems. Complexity science is not a single theory—it encompasses more than one theoretical framework and is highly interdisciplinary, seeking the answers to some fundamental questions about living, adaptable, changeable systems. Complex adaptive systems may adopt hard or softer approaches . Hard theories use formal language that is precise, tend to see agents as having tangible properties, and usually see objects in a behavioral system that can be manipulated in some way. Softer theories use natural language and narratives that may be imprecise, and agents are subjects having both tangible and intangible properties. Examples of hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and a class of softer theory is Viable System Theory. Many of the propositional consideration made in hard theory are also of relevance to softer theory. From here on, interest will now center on CAS.

复杂适应系统这个术语，或者复杂性科学（complexity science），经常被用来描述围绕此类系统研究而成长起来的松散组织的（这里”松散组织的“个人认为可以意译为”相关的“即可）学术领域。复杂性科学不是一个单一的理论——它包含不止一个理论框架，并且是高度跨学科的，目标是寻求一些关于活的、可适应的、可变的系统的基本问题的答案。针对复杂适应系统的研究可以采用硬方法或软方法：硬性理论使用精确的形式语言，倾向于认为代理人具有有形的属性，并且通常认为行为系统中的物体可以以某种方式被操纵；而软理论则使用自然语言和可能不精确的叙述，而代理人是同时具有有形和无形属性的主体。硬复杂性理论包括复杂适应系统理论和生存理论，其中一类较为软性的理论是生存系统理论。硬理论中提出的许多命题考虑也与软理论有关。自此之后，人们的研究兴趣将集中在复杂适应系统（CAS，Complex adaptive systems）上。

The study of CAS focuses on complex, emergent and macroscopic properties of the system.^[9]^[12]^[13] John H. Holland said that CAS "are systems that have a large numbers of components, often called agents, that interact and adapt or learn".^[14]

The study of CAS focuses on complex, emergent and macroscopic properties of the system.

复杂适应系统的研究主要集中在系统的复杂性、涌现性和宏观性上。

Typical examples of complex adaptive systems include: climate; cities; firms; markets; governments; industries; ecosystems; social networks; power grids; animal swarms; traffic flows; social insect (e.g. ant) colonies;^[15] the brain and the immune system; and the cell and the developing embryo. Human social group-based endeavors, such as political parties, communities, geopolitical organizations, war, and terrorist networks are also considered CAS.^[15]^[16]^[17] The internet and cyberspace—composed, collaborated, and managed by a complex mix of human–computer interactions, is also regarded as a complex adaptive system.^[18]^[19]^[20] CAS can be hierarchical, but more often exhibit aspects of "self-organization".^[21]

Typical examples of complex adaptive systems include: climate; cities; firms; markets; governments; industries; ecosystems; social networks; power grids; animal swarms; traffic flows; social insect (e.g. ant) colonies; The internet and cyberspace—composed, collaborated, and managed by a complex mix of human–computer interactions, is also regarded as a complex adaptive system.

复杂适应系统的典型例子包括: 气候、城市、企业、市场、政府、工业、生态系统、社交网络、电网、动物群落、交通流量、社会昆虫群体（例如：蚁群）等。除此之外，互联网和网络空间等由复杂的人机交互组成、协作和管理的网络系统也被视为复杂适应性系统。

一般性质 General properties

What distinguishes a CAS from a pure multi-agent system (MAS) is the focus on top-level properties and features like self-similarity, complexity, emergence and self-organization. A MAS is defined as a system composed of multiple interacting agents; whereas in CAS, the agents as well as the system are adaptive and the system is self-similar. A CAS is a complex, self-similar collectivity of interacting, adaptive agents. Complex Adaptive Systems are characterized by a high degree of adaptive capacity, giving them resilience in the face of perturbation.

复杂适应系统（CAS）与纯多智能体系统（MAS，Multi-agent system）的区别在于，CAS更关注顶级属性和特征，比如自相似性、复杂性、涌现性和自我组织。并且，多智能体系统是由多个相互作用的组件组成的系统，而在 CAS 系统中，组件与系统之间是自适应的，系统是自相似的。CAS是一个复杂的、自相似的、相互作用的自适应组件的集合。其特点就是具有高度的自适应能力，能够使其在面对干扰时具有一定的弹性。

Other important properties are adaptation (or homeostasis), communication, cooperation, specialization, spatial and temporal organization, and reproduction. They can be found on all levels: cells specialize, adapt and reproduce themselves just like larger organisms do. Communication and cooperation take place on all levels, from the agent to the system level. The forces driving co-operation between agents in such a system, in some cases, can be analyzed with game theory.

其他重要的属性分别是适应（或者说是内稳态（Homeostasis））、沟通、合作、专业化、时空组织和繁殖。这些特点可以在各个层面上被发现: 细胞分化、适应和繁殖，就像大型生物一样；沟通和合作也发生在各个层面，从代理到系统层面。在某些情况下，可以用博弈论（Game theory）分析这种系统中主体之间合作的驱动力。

特点 Characteristics

Some of the most important characteristics of complex systems are:^[22]

Some of the most important characteristics of complex systems are:

复杂系统的一些最重要的特征是:

The number of elements is sufficiently large that conventional descriptions (e.g. a system of differential equations) are not only impractical, but cease to assist in understanding the system. Moreover, the elements interact dynamically, and the interactions can be physical or involve the exchange of information

元素的数量足够大，以至于常规描述（如微分方程（Differential equation）系统）不仅不切实际，而且不再有助于理解该系统。此外，系统元素之间是动态交互的，并且这种交互既可以是物理的，也可以是信息交换；

Such interactions are rich, i.e. any element or sub-system in the system is affected by and affects several other elements or sub-systems

这样的交互是丰富的，即系统中的任何元素或子系统都受到并影响其他的元素或子系统；

The interactions are non-linear: small changes in inputs, physical interactions or stimuli can cause large effects or very significant changes in outputs

组件间相互作用是非线性（Non-linear）的：系统输入、组件间的物理相互作用或刺激的微小变化都可能会导致较大的影响，或使得输出发生非常显著的变化；

Interactions are primarily but not exclusively with immediate neighbours and the nature of the influence is modulated

相互作用以及受影响性质的调整主要但不仅限于其直接邻居；

Any interaction can feed back onto itself directly or after a number of intervening stages. Such feedback can vary in quality. This is known as recurrency

任何交互都可以直接或在多个干预阶段之后间接反馈到自身，此类反馈的质量可能会有所不同。这种现象称为重复发生（Recurrency）；

The overall behavior of the system of elements is not predicted by the behavior of the individual elements

元素系统的整体行为无法通过单个元素的行为来预测；

Such systems may be open and it may be difficult or impossible to define system boundaries

这样的系统可能是开放的，这使得我们很难或不可能定义系统的边界；

Complex systems operate under far from equilibrium conditions. There has to be a constant flow of energy to maintain the organization of the system

复杂系统在远非平衡的条件下运行，必须要有恒定的能量流来维持系统的组织；

Complex systems have a history. They evolve and their past is co-responsible for their present behaviour

复杂系统具有历史信息，它们不断演化发展，其历史信息对现在的系统行为具有一定的影响；

Elements in the system may be ignorant of the behaviour of the system as a whole, responding only to the information or physical stimuli available to them locally

系统中的某个元素可能并不了解整个系统的行为，因此会仅对本地可用的信息或物理刺激做出响应。

Robert Axelrod & Michael D. Cohen^[23] identify a series of key terms from a modeling perspective:

Robert Axelrod & Michael D. Cohen identify a series of key terms from a modeling perspective:

从建模的角度来看，罗伯特·阿克塞尔罗德(Robert Axelrod)和迈克尔·科恩(Michael D. Cohen)还确定了一系列关键术语:

Strategy, a conditional action pattern that indicates what to do in which circumstances

策略（Strategy）：一种有条件的行为模式，指示系统在什么情况下该做什么；

Artifact, a material resource that has definite location and can respond to the action of agents

工件（Artifact） （这里的专有名词的翻译有待商榷）：一种具有确定位置并可以响应代理行为的物质资源；

Agent, a collection of properties, strategies & capabilities for interacting with artifacts & other agents

主体（Agent）：用于与工件和其他代理进行交互的属性，策略和功能的集合；

Population, a collection of agents, or, in some situations, collections of strategies

群体（Population）：代理的集合，或在某些情况下，策略的集合；

System, a larger collection, including one or more populations of agents and possibly also artifacts

系统（System）：是一个较大的集合，包括一个或多个代理群体，可能还包括工件（artifacts）；

Type, all the agents (or strategies) in a population that have some characteristic in common

类型（Type）：总体中具有某些共同特征的所有主体（或策略）；

Variety, the diversity of types within a population or system

种类（Variety）：种群或系统中类型的多样性；

Interaction pattern, the recurring regularities of contact among types within a system

交互模式（Interaction pattern）：系统内类型之间的重复接触规律；

Space (physical), location in geographical space & time of agents and artifacts

空间（物理）（Space (physical)）：地理空间中的位置以及代理和人工制品的时间；

Space (conceptual), "location" in a set of categories structured so that "nearby" agents will tend to interact

空间（概念）（Space (conceptual)）：“位置”在一组结构合理的类别中，以便“附近”的代理进行交互；

Selection, processes that lead to an increase or decrease in the frequency of various types of agent or strategies

选择（Selection）：导致各种类型的代理或策略发生频率增加或减少的过程；

Success criteria or performance measures, a "score" used by an agent or designer in attributing credit in the selection of relatively successful (or unsuccessful) strategies or agents

成功标准（Success criteria） 或 评价指标（performance measures）：指评价代理或设计者在选择相对成功（或不成功）的策略或代理时的“分数”。

Turner and Baker^[24] synthesized the characteristics of complex adaptive systems from the literature and tested these characteristics in the context of creativity and innovation. Each of these eight characteristics had been shown to be present in the creativity and innovative processes:

Turner and Baker synthesized the characteristics of complex adaptive systems from the literature and tested these characteristics in the context of creativity and innovation. Each of these eight characteristics had been shown to be present in the creativity and innovative processes:

特纳（Turner）和贝克（Baker）从文献中综合了复杂适应系统的特征，并在创造力和创新的背景下测试了这些特征。这八个特点中的每一个都显示出在创造性和创新过程中存在:

Path dependent: Systems tend to be sensitive to their initial conditions. The same force might affect systems differently.^[25]

路径依赖（Path dependent）：系统状态对初始条件敏感，相同的力在不同初始条件下可能会对系统产生不同的影响；

Systems have a history: The future behavior of a system depends on its initial starting point and subsequent history.^[26]

系统具有历史记录（Systems have a history）：系统的未来行为取决于其初始状态和后续历史记录；

Non-linearity: React disproportionately to environmental perturbations. Outcomes differ from those of simple systems.^[27] ^[28]

非线性（Non-linearity）：对环境扰动的反应过大，结果与简单系统的结果不同；

Emergence: Each system's internal dynamics affect its ability to change in a manner that might be quite different from other systems.^[29]

涌现（Emergence）：每个系统内部动态影响其状态改变和改变能力的方式，可能与其他系统完全不同；

Irreducible: Irreversible process transformations cannot be reduced back to its original state.^[30]

不可还原（Irreducible） ：其过程转换是不可逆的，无法还原到其原始状态；

Adaptive/Adaptability: Systems that are simultaneously ordered and disordered are more adaptable and resilient.^[31]

适应性/适应性（Adaptive/Adaptability）：同时有序和无序的系统更具适应性和弹性；

Operates between order and chaos: Adaptive tension emerges from the energy differential between the system and its environment.^[32]

在有序和无序之间运行（Operates between order and chaos）：自适应张力是由系统与其所处环境之间的能量差产生的；

Self-organizing: Systems are composed of interdependency, interactions of its parts, and diversity in the system. ^[33]

自组织（Self-organizing） ：系统由相互依赖、相互作用的组件以及系统的多样性组成。

系统的建模与仿真 Modeling and simulation

CAS are occasionally modeled by means of agent-based models and complex network-based models.^[34] Agent-based models are developed by means of various methods and tools primarily by means of first identifying the different agents inside the model.^[35] Another method of developing models for CAS involves developing complex network models by means of using interaction data of various CAS components.^[36]

CAS are occasionally modeled by means of agent-based models and complex network-based models. Agent-based models are developed by means of various methods and tools primarily by means of first identifying the different agents inside the model. Another method of developing models for CAS involves developing complex network models by means of using interaction data of various CAS components.

复杂适应系统（CAS）有时可以用基于主体的模型（Agent-based model）和基于复杂网络的模型（Complex network-based models）来建模。基于主体的模型主要是通过识别模型中的不同主体，利用各种方法和工具开发的。而开发复杂适应系统模型的另一种方法，则是利用复杂适应系统各组成部分的交互数据来构建复杂的网络模型。

In 2013 SpringerOpen/BioMed Central has launched an online open-access journal on the topic of complex adaptive systems modeling (CASM).^[37]

In 2013 SpringerOpen/BioMed Central has launched an online open-access journal on the topic of complex adaptive systems modeling (CASM).

2013年，SpringerOpen/BioMed Central 推出了一个开放的在线获取期刊平台，其主题就是关于复杂适应性系统建模（CASM）。

复杂性的演变 Evolution of complexity

Passive versus active trends in the evolution of complexity. CAS at the beginning of the processes are colored red. Changes in the number of systems are shown by the height of the bars, with each set of graphs moving up in a time series.复杂性演进中的被动趋势与主动趋势。流程开始时的CAS颜色为红色。系统数量的变化通过条形图的高度显示，每组图按时间序列向上移动

Passive versus active trends in the evolution of complexity. CAS at the beginning of the processes are colored red. Changes in the number of systems are shown by the height of the bars, with each set of graphs moving up in a time series.

复杂性演变中的消极趋势与积极趋势如图所示。在进程的开始时整个CAS系统是红色的，系统数量的变化由条形图的高度来表示，每一组图在一个时间序列中向上移动。

Living organisms are complex adaptive systems. Although complexity is hard to quantify in biology, evolution has produced some remarkably complex organisms.^[38] This observation has led to the common misconception of evolution being progressive and leading towards what are viewed as "higher organisms".^[39]

Living organisms are complex adaptive systems. Although complexity is hard to quantify in biology, evolution has produced some remarkably complex organisms. This observation has led to the common misconception of evolution being progressive and leading towards what are viewed as "higher organisms".

活生物体是复杂的适应系统。尽管很难在生物学中量化复杂性，但进化确实产生了一些非常复杂的生物。这种现象导致对进化的普遍误解是”进化是渐进的，并产生了所谓的’高级生物‘“。

If this were generally true, evolution would possess an active trend towards complexity. As shown below, in this type of process the value of the most common amount of complexity would increase over time.^[40] Indeed, some artificial life simulations have suggested that the generation of CAS is an inescapable feature of evolution.^[41]^[42]

If this were generally true, evolution would possess an active trend towards complexity. As shown below, in this type of process the value of the most common amount of complexity would increase over time. Indeed, some artificial life simulations have suggested that the generation of CAS is an inescapable feature of evolution.

假设这种说法是普遍正确的，那么进化就会朝着复杂性的方向发展。如下所示，在这种类型的流程中，最常见的复杂性值会随着时间的推移而增加。而事实上，一些人工生命模拟已经表明，CAS的产生是进化过程中不可避免的特征。

However, the idea of a general trend towards complexity in evolution can also be explained through a passive process.^[40] This involves an increase in variance but the most common value, the mode, does not change. Thus, the maximum level of complexity increases over time, but only as an indirect product of there being more organisms in total. This type of random process is also called a bounded random walk.

However, the idea of a general trend towards complexity in evolution can also be explained through a passive process. This involves an increase in variance but the most common value, the mode, does not change. Thus, the maximum level of complexity increases over time, but only as an indirect product of there being more organisms in total. This type of random process is also called a bounded random walk.

然而，复杂性在进化中的普遍趋势的观点也可以通过一个被动的过程来解释。这涉及到方差的增加，但是最常见的值（即模式），并没有改变。因此，复杂性的最大水平随着时间的推移而增加，但仅仅是总体上有更多生物体的间接产物。这种随机过程也称为有界随机游走（Bounded random walk）。

In this hypothesis, the apparent trend towards more complex organisms is an illusion resulting from concentrating on the small number of large, very complex organisms that inhabit the right-hand tail of the complexity distribution and ignoring simpler and much more common organisms. This passive model emphasizes that the overwhelming majority of species are microscopic prokaryotes,^[43] which comprise about half the world's biomass^[44] and constitute the vast majority of Earth's biodiversity.^[45] Therefore, simple life remains dominant on Earth, and complex life appears more diverse only because of sampling bias.

In this hypothesis, the apparent trend towards more complex organisms is an illusion resulting from concentrating on the small number of large, very complex organisms that inhabit the right-hand tail of the complexity distribution and ignoring simpler and much more common organisms. This passive model emphasizes that the overwhelming majority of species are microscopic prokaryotes, which comprise about half the world's biomass and constitute the vast majority of Earth's biodiversity. Therefore, simple life remains dominant on Earth, and complex life appears more diverse only because of sampling bias.

在这一假设中，向更复杂的生物体发展的明显趋势是一种错觉，因为它只注意居住在复杂性分布的右端的少数大型、非常复杂的生物体，而忽略了更简单和更普通的生物体。这个被动模型强调，绝大多数物种是微小的原核生物，它们构成了世界生物量的一半，构成了地球生物多样性的绝大多数。因此，简单生命在地球上仍然占主导地位，而复杂生命仅仅因为抽样的偏差而显得更加多样化。

If there is a lack of an overall trend towards complexity in biology, this would not preclude the existence of forces driving systems towards complexity in a subset of cases. These minor trends would be balanced by other evolutionary pressures that drive systems towards less complex states.

如果在生物学中缺乏一个复杂性的总体趋势，这并不排除在一个子集的情况下驱动系统走向复杂性的力量的存在。这些小的趋势将被其他的进化压力所平衡，这些进化压力驱使系统朝着不那么复杂的状态发展。

参考文献 References

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