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第1行： + + + + − + − 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.<ref name="Miller, John H., and Scott E. Page">{{Cite book|title=Complex adaptive systems : an introduction to computational models of social life|last=Miller, John H., and Scott E. Page|date=2007-01-01|publisher=Princeton University Press|isbn=9781400835522|location=|pages=|oclc=760073369}}</ref> In complex adaptive systems, the whole is more complex than its parts,<ref>Holland, J. H. (1998). Emergence: From chaos to order. Reading, MA: Helix Books.</ref> and more complicated and meaningful than the aggregate of its parts. The study of complex adaptive systems, a subset of [[nonlinear dynamical system]]s,<ref name="Lansing 2003 pp. 183–204">{{cite journal | last=Lansing | first=J. Stephen | title=Complex Adaptive Systems | journal=Annual Review of Anthropology | publisher=Annual Reviews | volume=32 | issue=1 | year=2003 | issn=0084-6570 | doi=10.1146/annurev.anthro.32.061002.093440 | pages=183–204}}</ref> 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]].<ref>{{Cite news|url=http://www.slate.com/articles/technology/bitwise/2016/01/a_crude_look_at_the_whole_looks_at_complexity_theory_which_wants_to_understand.html|title=The Theory of Everything and Then Some|last=Auerbach|first=David|date=2016-01-19|work=Slate|access-date=2017-03-07|language=en-US|issn=1091-2339}}</ref> − − − 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. − − '''复杂适应系统 Complex adaptive system '''是一种系统，在这种系统中，对系统单个组成单元的理解并不能完美解释系统的整体行为<ref name="Miller, John H., and Scott E. Page">{{Cite book|title=Complex adaptive systems : an introduction to computational models of social life|last=Miller, John H., and Scott E. Page|date=2007-01-01|publisher=Princeton University Press|isbn=9781400835522|location=|pages=|oclc=760073369}}</ref>。在复杂适应系统中，系统的整体比其单独某个部分<ref>Holland, J. H. (1998). Emergence: From chaos to order. Reading, MA: Helix Books.</ref>或部分之和都更加复杂、更有意义。复杂适应系统是[[非线性动力系统]]的子集<ref name="Lansing 2003 pp. 183–204">{{cite journal | last=Lansing | first=J. Stephen | title=Complex Adaptive Systems | journal=Annual Review of Anthropology | publisher=Annual Reviews | volume=32 | issue=1 | year=2003 | issn=0084-6570 | doi=10.1146/annurev.anthro.32.061002.093440 | pages=183–204}}</ref>，其研究高度跨学科，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'''[[异质主体]] Heterogeneous agents'''、'''[[相变]] Phase transition '''和'''[[涌现行为]] Emergent behavior'''<ref>{{Cite news|url=http://www.slate.com/articles/technology/bitwise/2016/01/a_crude_look_at_the_whole_looks_at_complexity_theory_which_wants_to_understand.html|title=The Theory of Everything and Then Some|last=Auerbach|first=David|date=2016-01-19|work=Slate|access-date=2017-03-07|language=en-US|issn=1091-2339}}</ref> 。 − -- Heterogeneous agents翻译成“异构代理”不太合适，不太清楚应该怎么翻译。 − --[[用户:Yillia Jing|Yillia Jing]]（[[用户讨论:Yillia Jing|讨论]]）Heterogeneous agents翻译修改成了“异质主体" 第15行：
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第17行： − 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 [[life|living]], adaptable, changeable systems. Complex adaptive systems may adopt hard or softer approaches <ref>{{cite journal |last1=Yolles |first1=Maurice |title=The complexity continuum, Part 1: hard and soft theories |journal=Kybernetes |date=2018 |volume=48 |issue=6 |pages=1330–1354 |doi=10.1108/K-06-2018-0337}}</ref>. 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|Viability Theory]], and a class of softer theory is [[Viable_system_theory|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，倾向于认为主体本身具有有形的属性，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，而主体是同时具有有形和无形属性。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.<ref name="CAS-T-12" /><ref name="CAS-T-11" /><ref name="CAS-T-13" /> [[John Henry Holland|John H. Holland]] said that CAS "are systems that have a large numbers of components, often called agents, that interact and adapt or learn".<ref>{{cite journal|year=2006|title=Studying Complex Adaptive Systems|journal=Journal of Systems Science and Complexity|volume=19|issue=1|pages=1–8|doi=10.1007/s11424-006-0001-z|author=Holland John H|hdl=2027.42/41486|url=https://deepblue.lib.umich.edu/bitstream/2027.42/41486/1/11424_2006_Article_1.pdf}}</ref> − − 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、涌现性和宏观性质上。 第47行：
第34行： − 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 [[wikt:perturbation|perturbation]].+ − 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. − + − − − 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]]. − − 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. − − 复杂适应系统的其他重要属性分别是适应（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，从个体到系统层面。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。 + − − Some of the most important characteristics of complex systems are:<ref>[[Paul Cilliers]] (1998) ''Complexity and Postmodernism: Understanding Complex Systems''</ref> − − 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 equation]]s) 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 − * 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 − * The interactions are [[non-linear]]: small changes in inputs, physical interactions or stimuli can cause large effects or very significant changes in outputs − * Interactions are primarily but not exclusively with immediate neighbours and the nature of the influence is modulated − * 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'' − * The overall behavior of the system of elements is not predicted by the behavior of the individual elements − * Such systems may be open and it may be difficult or impossible to define system boundaries − * Complex systems operate under [[Non-equilibrium thermodynamics|far from equilibrium]] conditions. There has to be a constant flow of energy to maintain the organization of the system − * Complex systems have a history. They evolve and their past is co-responsible for their present behaviour − * 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 + − [[Robert Axelrod]] & [[Michael D. Cohen (academic)|Michael D. Cohen]]<ref>[[Robert Axelrod]] & [[Michael D. Cohen (academic)|Michael D. Cohen]], ''Harnessing Complexity''. [[Basic Books]], 2001</ref> 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 − * '''Artifact''', a material resource that has definite location and can respond to the action of agents − * '''Agent''', a collection of properties, strategies & capabilities for interacting with artifacts & other agents − * '''Population''', a collection of agents, or, in some situations, collections of strategies − + − * '''System''', a larger collection, including one or more populations of agents and possibly also artifacts − + − * '''Type''', all the agents (or strategies) in a population that have some characteristic in common − * '''Variety''', the diversity of types within a population or system − * '''Interaction pattern''', the recurring regularities of contact among types within a system − * '''Space (physical)''', location in geographical space & time of agents and artifacts − * '''Space (conceptual)''', "location" in a set of categories structured so that "nearby" agents will tend to interact − * '''Selection''', processes that lead to an increase or decrease in the frequency of various types of agent or strategies − * '''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 + − Turner and Baker<ref>Turner, J. R., & Baker, R. (in press). Just doing the do: A case study testing creativity and innovative processes as complex adaptive systems. New Horizons in Adult Education and Human Resource Development.</ref> 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: − + − * '''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； − + − * '''系统具有历史 Systems have a history'''：系统的未来行为取决于其初始状态和后续的历史； − + − * '''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； − + − * '''涌现 Emergence'''：每个系统内部动力学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； − + − * '''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； − + − * '''适应性/适应能力 Adaptive/Adaptability'''：同时处于有序和无序状态的系统更具适应性和恢复力； − + − * '''在有序和混沌之间运行 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. <ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref> − − * '''自组织 Self-organizing''' ：系统由相互依赖、相互作用的组成部分以及系统的多样性组成。 − CAS are occasionally modeled by means of [[agent-based model]]s and [[complex network]]-based models.<ref>Muaz A. K. Niazi, Towards A Novel Unified Framework for Developing Formal, Network and Validated Agent-Based Simulation Models of Complex Adaptive Systems [https://dspace.stir.ac.uk/handle/1893/3365 PhD Thesis]</ref> Agent-based models are developed by means of various methods and tools primarily by means of first identifying the different agents inside the model.<ref>John H. Miller & Scott E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press [http://press.princeton.edu/titles/8429.html Book page]</ref> Another method of developing models for CAS involves developing complex network models by means of using interaction data of various CAS components.<ref>Melanie Mitchell, Complexity A Guided Tour, Oxford University Press, [http://www.oup.com/us/catalog/general/subject/LifeSciences/~~/dmlldz11c2EmY2k9OTc4MDE5NTEyNDQxNQ== Book page]</ref>+ − − 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. − − 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|SpringerOpen/BioMed Central]] has launched an online open-access journal on the topic of ''complex adaptive systems modeling'' (CASM).<ref>Springer ''[https://casmodeling.springeropen.com/ Complex Adaptive Systems Modeling Journal]'' (CASM)</ref> − 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'''。 − + − 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. − − + − Living organisms are complex adaptive systems. Although complexity is hard to quantify in biology, [[evolution]] has produced some remarkably complex organisms.<ref>{{cite journal |author=Adami C |title=What is complexity? |journal=BioEssays |volume=24 |issue=12 |pages=1085–94 |year=2002 |pmid=12447974 |doi=10.1002/bies.10192}}</ref> This observation has led to the common misconception of evolution being progressive and leading towards what are viewed as "higher organisms".<ref>{{cite journal |author=McShea D |title=Complexity and evolution: What everybody knows |journal=Biology and Philosophy |volume=6 |issue=3 |pages=303–24 |year=1991 |doi=10.1007/BF00132234}}</ref> − 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".+ − 生命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.<ref name=Carroll>{{cite journal |author=Carroll SB |title=Chance and necessity: the evolution of morphological complexity and diversity |journal=Nature |volume=409 |issue=6823 |pages=1102–9 |year=2001 |pmid=11234024 |doi=10.1038/35059227|bibcode = 2001Natur.409.1102C }}</ref> Indeed, some [[artificial life]] simulations have suggested that the generation of CAS is an inescapable feature of evolution.<ref>{{cite journal |vauthors=Furusawa C, Kaneko K |title=Origin of complexity in multicellular organisms |journal=Phys. Rev. Lett. |volume=84 |issue=26 Pt 1 |pages=6130–3 |year=2000 |pmid=10991141 |doi=10.1103/PhysRevLett.84.6130 |bibcode=2000PhRvL..84.6130F|arxiv = nlin/0009008 }}</ref><ref>{{cite journal |vauthors=Adami C, Ofria C, Collier TC |title=Evolution of biological complexity |journal=Proc. Natl. Acad. Sci. U.S.A. |volume=97 |issue=9 |pages=4463–8 |year=2000 |pmid=10781045 |doi=10.1073/pnas.97.9.4463 |pmc=18257|arxiv = physics/0005074 |bibcode = 2000PNAS...97.4463A }}</ref> − − 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的方向发展。如下所示，在这类过程中，最常见的复杂性程度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.<ref name=Carroll/> This involves an increase in [[variance]] but the most common value, the [[mode (statistics)|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. + − 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 [[Skewness|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 [[microorganism|microscopic]] [[prokaryote]]s,<ref>{{cite journal |author=Oren A |title=Prokaryote diversity and taxonomy: current status and future challenges |pmc=1693353 |journal=Philos. Trans. R. Soc. Lond. B Biol. Sci. |volume=359 |issue=1444 |pages=623–38 |year=2004 |pmid=15253349 |doi=10.1098/rstb.2003.1458}}</ref> which comprise about half the world's [[biomass]]<ref>{{cite journal |vauthors=Whitman W, Coleman D, Wiebe W | title = Prokaryotes: the unseen majority | journal = Proc Natl Acad Sci USA | volume = 95 | issue = 12 | pages = 6578–83 | year = 1998 |pmid = 9618454 | doi = 10.1073/pnas.95.12.6578 | pmc = 33863|bibcode = 1998PNAS...95.6578W }}</ref> and constitute the vast majority of Earth's biodiversity.<ref>{{cite journal |vauthors=Schloss P, Handelsman J |title=Status of the microbial census |pmc=539005 |journal=Microbiol Mol Biol Rev |volume=68 |issue=4 |pages=686–91 |year=2004 |pmid=15590780 |doi=10.1128/MMBR.68.4.686-691.2004}}</ref> 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，因为它只注意到了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. − − 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. 第276行：
第175行： − {{Portal| 系统科学 Systems science}} 第307行：
第205行： − − * [[Wicked problem|Super wicked problem]] 第317行：
第213行： − + − {{Reflist|2|refs= − − {{Reflist|2|refs= − − {通货再膨胀 | 2 | refs = 第348行：
第239行： − + − − <ref name=CAS-T-17>{{cite web|title=Cyberspace: The Ultimate Complex Adaptive System|url=http://www.dodccrp.org/files/IC2J_v4n2_03_Phister.pdf|publisher=The International C2 Journal − − 17 > { cite web | title = Cyberspace: The Ultimate 复杂适应性系统 | url = http://www.dodccrp.org/files/ic2j_v4n2_03_phister.pdf|publisher=The 国际 C2期刊 − − |accessdate=25 August 2012}} by Paul W. Phister Jr</ref> − − − − 25 August 2012} by Paul w. phistr </ref > − 第372行：
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第304行： + + + − {{Systems}} − − − − {{DEFAULTSORT:Complex Adaptive System}} − − [[Category:Complex systems theory]] − − Category:Complex systems theory − − 范畴: 复杂系统理论 − − [[Category:Systems science]] − − Category:Systems science − − 类别: 系统科学 − − [[Category:Organizational theory|*]] − − * − − * − <noinclude>+ − <small>This page was moved from [[wikipedia:en:Complex adaptive system]]. Its edit history can be viewed at [[复杂适应系统/edithistory]]</small></noinclude> − +
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'''复杂适应系统 Complex adaptive system '''(CAS)是一种系统，在这种系统中，对系统单个组成单元的理解并不能完美解释系统的整体行为<ref name="Miller, John H., and Scott E. Page">{{Cite book|title=Complex adaptive systems : an introduction to computational models of social life|last=Miller, John H., and Scott E. Page|date=2007-01-01|publisher=Princeton University Press|isbn=9781400835522|location=|pages=|oclc=760073369}}</ref>。在复杂适应系统中，系统的整体比其单独某个部分<ref>Holland, J. H. (1998). Emergence: From chaos to order. Reading, MA: Helix Books.</ref>或部分之和都更加复杂、更有意义。复杂适应系统是[[非线性动力系统]]的子集<ref name="Lansing 2003 pp. 183–204">{{cite journal | last=Lansing | first=J. Stephen | title=Complex Adaptive Systems | journal=Annual Review of Anthropology | publisher=Annual Reviews | volume=32 | issue=1 | year=2003 | issn=0084-6570 | doi=10.1146/annurev.anthro.32.061002.093440 | pages=183–204}}</ref>，其研究高度跨学科，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'''[[异质主体]] Heterogeneous agents'''、'''[[相变]] Phase transition '''和'''[[涌现行为]] Emergent behavior'''<ref>{{Cite news|url=http://www.slate.com/articles/technology/bitwise/2016/01/a_crude_look_at_the_whole_looks_at_complexity_theory_which_wants_to_understand.html|title=The Theory of Everything and Then Some|last=Auerbach|first=David|date=2016-01-19|work=Slate|access-date=2017-03-07|language=en-US|issn=1091-2339}}</ref> 。
They are ''[[complex system|complex]]'' in that they are [[Dynamic network analysis|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-organizing|self-organize]] corresponding to the change-initiating micro-event or collection of events.<ref name=CAS-T-01/><ref name=CAS-T-02/><ref name="Miller, John H., and Scott E. Page"/> They are a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to [[Adaptive system|adapt]] to the changing environment and increase their survivability as a [[macrostructure (sociology)|macro-structure]].<ref name=CAS-T-01/><ref name=CAS-T-02/><ref name=CAS-T-12/> The Complex Adaptive Systems approach builds on [[replicator dynamics]].<ref>{{cite journal |last1=Foster |first1=John |date=2006 |title=Why is economics not a complex systems science? |url=https://espace.library.uq.edu.au/view/UQ:9953/econ_dp_336_04.pdf |journal=Journal of Economic Issues |volume=40 |issue=4 |pages=1069-1091 |doi=10.1080/00213624.2006.11506975 |access-date=2020-01-18 }}</ref>
They are ''[[complex system|complex]]'' in that they are [[Dynamic network analysis|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-organizing|self-organize]] corresponding to the change-initiating micro-event or collection of events.<ref name=CAS-T-01/><ref name=CAS-T-02/><ref name="Miller, John H., and Scott E. Page"/> They are a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to [[Adaptive system|adapt]] to the changing environment and increase their survivability as a [[macrostructure (sociology)|macro-structure]].<ref name=CAS-T-01/><ref name=CAS-T-02/><ref name=CAS-T-12/> The Complex Adaptive Systems approach builds on [[replicator dynamics]].<ref>{{cite journal |last1=Foster |first1=John |date=2006 |title=Why is economics not a complex systems science? |url=https://espace.library.uq.edu.au/view/UQ:9953/econ_dp_336_04.pdf |journal=Journal of Economic Issues |volume=40 |issue=4 |pages=1069-1091 |doi=10.1080/00213624.2006.11506975 |access-date=2020-01-18 }}</ref>
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.
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。
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。<ref name=CAS-T-01/><ref name=CAS-T-02/><ref name="Miller, John H., and Scott E. Page"/> 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 ==
== 概述 Overview ==
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<ref>{{cite journal |last1=Yolles |first1=Maurice |title=The complexity continuum, Part 1: hard and soft theories |journal=Kybernetes |date=2018 |volume=48 |issue=6 |pages=1330–1354 |doi=10.1108/K-06-2018-0337}}</ref>：硬性理论使用精确的形式语言，倾向于认为主体本身具有有形的属性，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，而主体是同时具有有形和无形属性。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'''上。
复杂适应系统的研究主要集中在系统的复杂性、涌现性和宏观性质上。<ref name="CAS-T-12" /><ref name="CAS-T-11" /><ref name="CAS-T-13" />
=== 一般性质 General properties ===
=== 一般性质 General properties ===
'''复杂适应系统(CAS)'''与'''纯多智能体系统 Multi-agent system(MAS)'''的区别在于，CAS更关注顶层性质和特征，比如自相似性、复杂性、涌现性和自组织。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恢复能力。
'''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更关注顶层性质和特征，比如自相似性、复杂性、涌现性和自组织。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恢复能力。
复杂适应系统的其他重要属性分别是适应（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，从个体到系统层面。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 ===
=== 特点 Characteristics ===
复杂系统的一些最重要的特征是:<ref>[[Paul Cilliers]] (1998) ''Complexity and Postmodernism: Understanding Complex Systems''</ref>
* 个体的数量足够大，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，系统个体之间发生动力学上的相互作用，并且这种相互作用既可以是物理的，也可以是信息的交换；
* 个体的数量足够大，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，系统个体之间发生动力学上的相互作用，并且这种相互作用既可以是物理的，也可以是信息的交换；
* 这样的相互作用是丰富的，即系统中的任何个体或子系统都受到并影响其他的个体或子系统；
* 这样的相互作用是丰富的，即系统中的任何个体或子系统都受到并影响其他的个体或子系统；
* 个体间相互作用是'''非线性 Non-linear'''的：系统输入、个体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；
* 个体间相互作用是'''非线性 Non-linear'''的：系统输入、个体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；
* 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；
* 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；
* 任何相互作用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'''；
* 任何相互作用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'''；
* 系统的整体行为无法通过单个个体的行为来预测；
* 系统的整体行为无法通过单个个体的行为来预测；
* 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；
* 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；
* 复杂系统在非平衡态（远离平衡态）的条件下运行，必须要有恒定的能量流来维持系统的组织；
* 复杂系统在非平衡态（远离平衡态）的条件下运行，必须要有恒定的能量流来维持系统的组织；
* 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；
* 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；
* 系统中的个体可能并不了解整个系统的行为，因此仅会对局域的可用信息或物理刺激做出响应。
* 系统中的个体可能并不了解整个系统的行为，因此仅会对局域的可用信息或物理刺激做出响应。
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'''<ref>[[Robert Axelrod]] & [[Michael D. Cohen (academic)|Michael D. Cohen]], ''Harnessing Complexity''. [[Basic Books]], 2001</ref> 还确定了一系列关键术语:
* '''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；
* '''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；
* '''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个体行为的物质资源；
* '''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个体行为的物质资源；
* '''主体 Agent'''：用于与工件和其他个体进行交互的属性，策略和功能的集合；
* '''主体 Agent'''：用于与工件和其他个体进行交互的属性，策略和功能的集合；
* '''群体 （建议翻译为：种群）Population'''：个体的集合，或在某些情况下，策略的集合；
* '''种群 Population'''：个体的集合，或在某些情况下，策略的集合；
* '''系统 System'''：是一个较大的集合，包括一个或多个个体的群体，可能还包括工件（artifacts）；
* '''系统 System'''：是一个较大的集合，包括一个或多个个体的群体，可能还包括工件 artifacts ；
* '''类型 Type'''：总体中具有某些共同特征的所有主体（或策略）；
* '''类型 Type'''：总体中具有某些共同特征的所有主体（或策略）；
* '''种类 Variety'''：种群或系统中类型的多样性；
* '''种类 Variety'''：种群或系统中类型的多样性；
* '''交互模式 Interaction pattern'''：系统内类型之间的重复接触规律；
* '''交互模式 Interaction pattern'''：系统内类型之间的重复接触规律；
* '''空间（物理） Space (physical)'''：个体和工件在地理空间或时间中的位置；
* '''空间（物理） Space (physical)'''：个体和工件在地理空间或时间中的位置；
* '''空间（概念） Space (conceptual)'''：“位置”在一组结构合理的类别中，以便“附近”的个体进行交互；
* '''空间（概念） Space (conceptual)'''：“位置”在一组结构合理的类别中，以便“附近”的个体进行交互；
* '''选择 Selection'''：导致各种类型的个体或策略发生频率增加或减少的过程；
* '''选择 Selection'''：导致各种类型的个体或策略发生频率增加或减少的过程；
* '''成功标准 Success criteria''' 或 '''评价指标 Performance measures'''：指评价个体或设计者在选择相对成功（或不成功）的策略或个体时的“分数”。
* '''成功标准 Success criteria''' 或 '''评价指标 Performance measures'''：指评价个体或设计者在选择相对成功（或不成功）的策略或个体时的“分数”。
'''特纳 Turner'''和'''贝克 Baker'''<ref>Turner, J. R., & Baker, R. (in press). Just doing the do: A case study testing creativity and innovative processes as complex adaptive systems. New Horizons in Adult Education and Human Resource Development.</ref>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:
* '''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；<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref>
* '''Path dependent:''' Systems tend to be sensitive to their initial conditions. The same force might affect systems differently.<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref>
* '''系统具有历史 Systems have a history'''：系统的未来行为取决于其初始状态和后续的历史；<ref>{{cite journal | last1 = Boal | first1 = K. B. | last2 = Schultz | first2 = P. L. | year = 2007 | title = Storytelling, time, and evolution: The role of strategic leadership in complex adaptive systems | url = | journal = The Leadership Quarterly | volume = 18 | issue = 4| pages = 411–428 | doi = 10.1016/j.leaqua.2007.04.008 }}</ref>
* '''Systems have a history:''' The future behavior of a system depends on its initial starting point and subsequent history.<ref>{{cite journal | last1 = Boal | first1 = K. B. | last2 = Schultz | first2 = P. L. | year = 2007 | title = Storytelling, time, and evolution: The role of strategic leadership in complex adaptive systems | url = | journal = The Leadership Quarterly | volume = 18 | issue = 4| pages = 411–428 | doi = 10.1016/j.leaqua.2007.04.008 }}</ref>
* '''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；<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref> <ref>{{cite journal | last1 = Luoma | first1 = M | year = 2006 | title = A play of four arenas - How complexity can serve management development | url = | journal = Management Learning | volume = 37 | issue = | pages = 101–123 | doi = 10.1177/1350507606058136 }}</ref>
* '''Non-linearity:''' React disproportionately to environmental perturbations. Outcomes differ from those of simple systems.<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref> <ref>{{cite journal | last1 = Luoma | first1 = M | year = 2006 | title = A play of four arenas - How complexity can serve management development | url = | journal = Management Learning | volume = 37 | issue = | pages = 101–123 | doi = 10.1177/1350507606058136 }}</ref>
* '''涌现 Emergence'''：每个系统内部动力学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；<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref>
* '''Emergence:''' Each system's internal dynamics affect its ability to change in a manner that might be quite different from other systems.<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref>
* '''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；<ref>{{cite journal | last1 = Borzillo | first1 = S. | last2 = Kaminska-Labbe | first2 = R. | year = 2011 | title = Unravelling the dynamics of knowledge creation in communities of practice through complexity theory lenses | url = | journal = Knowledge Management Research & Practice | volume = 9 | issue = | pages = 353–366 | doi = 10.1057/kmrp.2011.13 }}</ref>
* '''Irreducible:''' Irreversible process transformations cannot be reduced back to its original state.<ref>{{cite journal | last1 = Borzillo | first1 = S. | last2 = Kaminska-Labbe | first2 = R. | year = 2011 | title = Unravelling the dynamics of knowledge creation in communities of practice through complexity theory lenses | url = | journal = Knowledge Management Research & Practice | volume = 9 | issue = | pages = 353–366 | doi = 10.1057/kmrp.2011.13 }}</ref>
* '''适应性/适应能力 Adaptive/Adaptability'''：同时处于有序和无序状态的系统更具适应性和恢复力；<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref>
* '''Adaptive/Adaptability:''' Systems that are simultaneously ordered and disordered are more adaptable and resilient.<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref>
* '''在有序和混沌之间运行 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；<ref>{{cite journal | last1 = Borzillo | first1 = S. | last2 = Kaminska-Labbe | first2 = R. | year = 2011 | title = Unravelling the dynamics of knowledge creation in communities of practice through complexity theory lenses | url = | journal = Knowledge Management Research & Practice | volume = 9 | issue = | pages = 353–366 | doi = 10.1057/kmrp.2011.13 }}</ref>
* '''Operates between order and chaos:''' Adaptive tension emerges from the energy differential between the system and its environment.<ref>{{cite journal | last1 = Borzillo | first1 = S. | last2 = Kaminska-Labbe | first2 = R. | year = 2011 | title = Unravelling the dynamics of knowledge creation in communities of practice through complexity theory lenses | url = | journal = Knowledge Management Research & Practice | volume = 9 | issue = | pages = 353–366 | doi = 10.1057/kmrp.2011.13 }}</ref>
* '''自组织 Self-organizing''' ：系统由相互依赖、相互作用的组成部分以及系统的多样性组成。<ref>{{cite journal | last1 = Lindberg | first1 = C. | last2 = Schneider | first2 = M. | year = 2013 | title = Combating infections at Maine Medical Center: Insights into complexity-informed leadership from positive deviance | url = | journal = Leadership | volume = 9 | issue = 2| pages = 229–253 | doi = 10.1177/1742715012468784 }}</ref>
== 系统的建模与仿真 Modeling and simulation ==
== 系统的建模与仿真 Modeling and simulation ==
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。<ref>Muaz A. K. Niazi, Towards A Novel Unified Framework for Developing Formal, Network and Validated Agent-Based Simulation Models of Complex Adaptive Systems [https://dspace.stir.ac.uk/handle/1893/3365 PhD Thesis]</ref>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。<ref>John H. Miller & Scott E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press [http://press.princeton.edu/titles/8429.html Book page]</ref> 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。<ref>Melanie Mitchell, Complexity A Guided Tour, Oxford University Press, [http://www.oup.com/us/catalog/general/subject/LifeSciences/~~/dmlldz11c2EmY2k9OTc4MDE5NTEyNDQxNQ== Book page]</ref>
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)'''。<ref>Springer ''[https://casmodeling.springeropen.com/ Complex Adaptive Systems Modeling Journal]'' (CASM)</ref>
== 复杂性的演变 Evolution of complexity ==
== 复杂性的演变 Evolution of complexity ==
[[File:Evolutionofcomplexity.png|thumb|300px|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]]
[[File:Evolutionofcomplexity.png|thumb|300px|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]]
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。
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。
{{Main|Evolution of biological complexity}}
{{Main|Evolution of biological complexity}}
生命体是复杂的适应系统。 尽管很难在生物学中量化复杂性，.<ref>{{cite journal |author=Adami C |title=What is complexity? |journal=BioEssays |volume=24 |issue=12 |pages=1085–94 |year=2002 |pmid=12447974 |doi=10.1002/bies.10192}}</ref>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‘“。<ref>{{cite journal |author=McShea D |title=Complexity and evolution: What everybody knows |journal=Biology and Philosophy |volume=6 |issue=3 |pages=303–24 |year=1991 |doi=10.1007/BF00132234}}</ref>
假设这种说法是普遍正确的，那么进化就会朝着复杂的方向发展。如下所示，在这类过程中，最常见的复杂性程度会随着时间的推移而增加。<ref name=Carroll>{{cite journal |author=Carroll SB |title=Chance and necessity: the evolution of morphological complexity and diversity |journal=Nature |volume=409 |issue=6823 |pages=1102–9 |year=2001 |pmid=11234024 |doi=10.1038/35059227|bibcode = 2001Natur.409.1102C }}</ref>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。<ref>{{cite journal |vauthors=Furusawa C, Kaneko K |title=Origin of complexity in multicellular organisms |journal=Phys. Rev. Lett. |volume=84 |issue=26 Pt 1 |pages=6130–3 |year=2000 |pmid=10991141 |doi=10.1103/PhysRevLett.84.6130 |bibcode=2000PhRvL..84.6130F|arxiv = nlin/0009008 }}</ref><ref>{{cite journal |vauthors=Adami C, Ofria C, Collier TC |title=Evolution of biological complexity |journal=Proc. Natl. Acad. Sci. U.S.A. |volume=97 |issue=9 |pages=4463–8 |year=2000 |pmid=10781045 |doi=10.1073/pnas.97.9.4463 |pmc=18257|arxiv = physics/0005074 |bibcode = 2000PNAS...97.4463A }}</ref>
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'''。
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'''。
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，因为它只注意到了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，<ref>{{cite journal |author=Oren A |title=Prokaryote diversity and taxonomy: current status and future challenges |pmc=1693353 |journal=Philos. Trans. R. Soc. Lond. B Biol. Sci. |volume=359 |issue=1444 |pages=623–38 |year=2004 |pmid=15253349 |doi=10.1098/rstb.2003.1458}}</ref>它们构成了世界生物量的一半，<ref>{{cite journal |vauthors=Whitman W, Coleman D, Wiebe W | title = Prokaryotes: the unseen majority | journal = Proc Natl Acad Sci USA | volume = 95 | issue = 12 | pages = 6578–83 | year = 1998 |pmid = 9618454 | doi = 10.1073/pnas.95.12.6578 | pmc = 33863|bibcode = 1998PNAS...95.6578W }}</ref> 构成了地球生物多样性的绝大多数。<ref>{{cite journal |vauthors=Schloss P, Handelsman J |title=Status of the microbial census |pmc=539005 |journal=Microbiol Mol Biol Rev |volume=68 |issue=4 |pages=686–91 |year=2004 |pmid=15590780 |doi=10.1128/MMBR.68.4.686-691.2004}}</ref> 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。
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。
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。
== 相关概念 See also ==
== 相关概念 See also ==
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{{div col|colwidth=30em}}
* [[社会学与复杂性科学 Sociology and complexity science]]
* [[社会学与复杂性科学 Sociology and complexity science]]
* [[群开发小组 Swarm Development Group]]
* [[群开发小组 Swarm Development Group]]
== 参考文献 References==
== 参考文献 References==
<references/>
<ref name=CAS-T-01>{{cite web |url=http://tejas.iimb.ac.in/articles/12.php|title=Insights from Complexity Theory: Understanding Organisations better |publisher= by Assoc. Prof. Amit Gupta, Student contributor - S. Anish, IIM Bangalore|date= |accessdate=1 June 2012 }}</ref>
<ref name=CAS-T-01>{{cite web |url=http://tejas.iimb.ac.in/articles/12.php|title=Insights from Complexity Theory: Understanding Organisations better |publisher= by Assoc. Prof. Amit Gupta, Student contributor - S. Anish, IIM Bangalore|date= |accessdate=1 June 2012 }}</ref>
<ref name=CAS-T-17>{{cite web|title=Cyberspace: The Ultimate Complex Adaptive System|url=http://www.dodccrp.org/files/IC2J_v4n2_03_Phister.pdf|publisher=The International C2 Journal
<ref name=CAS-T-17>{{cite web|title=Cyberspace: The Ultimate Complex Adaptive System|url=http://www.dodccrp.org/files/IC2J_v4n2_03_Phister.pdf|publisher=The International C2 Journal|accessdate=25 August 2012}} by Paul W. Phister Jr</ref>
|accessdate=25 August 2012}} by Paul W. Phister Jr</ref>
<ref name=GT-33>{{cite web|title=Toward a Complex Adaptive Intelligence Community The Wiki and the Blog|url=https://www.cia.gov/library/center-for-the-study-of-intelligence/csi-publications/csi-studies/studies/vol49no3/html_files/Wik_and_%20Blog_7.htm|work=D. Calvin Andrus|publisher=cia.gov|accessdate=25 August 2012}}</ref>
<ref name=GT-33>{{cite web|title=Toward a Complex Adaptive Intelligence Community The Wiki and the Blog|url=https://www.cia.gov/library/center-for-the-study-of-intelligence/csi-publications/csi-studies/studies/vol49no3/html_files/Wik_and_%20Blog_7.htm|work=D. Calvin Andrus|publisher=cia.gov|accessdate=25 August 2012}}</ref>
== 其他参考资料 Literature ==
== 其他参考资料 Literature ==
==编者推荐==
====[https://campus.swarma.org/course/1004 演化与适应：从存在到演化]
本课程将介绍关于系统的动力学与复杂系统的演化。
[[Category:复杂系统理论]]
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[[Category:系统科学]]