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大多数复杂系统模型通常是根据统计物理学、信息论和非线性动力学的概念来制定的；这些方法并不关注或者说不包括与组织、拓扑属性或代数拓扑有关的复杂性的概念部分，如基因组、交互体和生物有机体的[[网络连通性]]这些重要概念<ref name="Rosen" /><ref>^ Heylighen, Francis (2008). "Complexity and Self-Organization". In Bates, Marcia J.; Maack, Mary Niles. Encyclopedia of Library and Information Sciences. CRC.</ref><ref>"abstract relational biology (ARB)". PlanetPhysics. Retrieved 2010-03-17.</ref>。近年来，人们把以信息论、网络拓扑/抽象图论概念为基础的两种互补方法在神经科学和人类认知等领域结合起来<ref name="springerlink" /><ref>http://hdl.handle.net/10101/npre.2011.6115.1 Wallace, Rodrick. When Spandrels Become Arches: Neural crosstalk and the evolution of consciousness. Available from Nature Precedings  (2011)</ref>。人们普遍认为，组织的复杂程度存在一种应与本体论的现实层次相区别层次结构<ref name="springerlink" /><ref>{{cite journal | author = Poli R | year = 2001a | title = The Basic Problem of the Theory of Levels of Reality | url = | journal = Axiomathes | volume = 12 | issue = 3–4| pages = 261–283 | doi = 10.1023/A:1015845217681 }}</ref><ref>{{cite journal | author = Poli R | year = 1998 | title = Levels | url = | journal = Axiomathes | volume = 9 | issue = 1–2| pages = 197–211 | doi=10.1007/bf02681712| pmid = 8053082 }}</ref>，现代等级分类的分类方法也承认生物圈的例如：生物领域和生物圈、生物的界、门、纲、目、科、属和种等复杂层次结构。由于生物体具有动态性和组成的可变性、内在的“模糊性”、自生属性、自我繁殖的能力等等，生物体不符合一般系统的“标准”的定义，因此它们在功能和结构上都是“超级复杂”的；因此，在CSB中，生物体只能被定义为一种简单动态系统，“元系统”<ref name="springerlink" /><ref>[http://pespmc1.vub.ac.be/MST.html Metasystem Transition Theory], Valentin Turchin, Cliff Joslyn, 1993-1997</ref>。这样一个有机体、物种、“生态系统”等等的元系统定义 ,如自生系统理论中所述的系统的系统<ref>[http://archonic.net Reflexive Autopoietic Systems Theory]</ref>。它也不同于K·D·帕尔默在元系统工程中提出的定义<ref>[http://archonic.net/incosewg/ppframe.htm Meta-system Engineering], Kent D. Palmer, 1996</ref>，即生物体不同于具有固定输入输出转换函数的机器和自动机，或不同于具有固定相空间的连续动力系统<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A Framework for Systems with Dynamic Topology. ''International Journal of Computing Anticipatory System's'' 14:259–270</ref>，这与笛卡尔哲学思想相反；因此，尽管“非确定性自动机”和“模糊自动机”也被定义了，但生物体不能仅仅用五组a（状态、启动状态、输入和输出集/字母、转换函数）来定义<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A Framework for Systems with Dynamic Topology. ''International Journal of Computing Anticipatory System's'' 14:259–270</ref>。然而，棋盘自动机 tessellation automata或[[元胞自动机 cellular automata]] 提供了一种直观的、可视化的/计算的视角来洞察较低层次的复杂性，因此已经成为一种越来越流行的离散模型，研究领域包括可计算理论、应用数学、物理、计算机科学、理论生物学/系统生物学、癌症模拟和微观结构建模。利用[[遗传算法]]<ref>The Evolutionary Design of Collective Computation in Cellular Automata, James P. Crutchfeld, Melanie Mitchell, Rajarshi Das (In J. P. Crutchfield and P. K. Schuster (editors), Evolutionary Dynamics|Exploring the Interplay of Selection, Neutrality, Accident, and Function. New York: Oxford University Press, 2002.)</ref><ref>Evolving Cellular Automata with Genetic Algorithms: A Review of Recent Work, Melanie Mitchell, James P. Crutchfeld, Rajarshi Das (In Proceedings of the First International Conference on Evolutionary Computation and Its Applications (EvCA'96). Moscow, Russia: Russian Academy of Sciences, 1996.)</ref><ref>{{cite journal | doi = 10.1073/pnas.0307811100 | last1 = Peak | first1 = West | last2 = Messinger | first2 = Mott | year = 2004 | title = Evidence for complex, collective dynamics and emergent, distributed computation in plants | journal = Proceedings of the National Academy of Sciences of the USA | volume = 101 | issue = 4| pages = 918–922 |bibcode = 2004PNAS..101..918P | pmid = 14732685 | last3 = Messinger | first3 = SM | last4 = Mott | first4 = KA | pmc = 327117}}</ref> 实现元胞自动机是一个桥接棋盘自动机和CSB中的高层次复杂性方法之间差距的新兴领域。

大多数复杂系统模型通常是根据统计物理学、信息论和非线性动力学的概念来制定的；这些方法并不关注或者说不包括与组织、拓扑属性或代数拓扑有关的复杂性的概念部分，如基因组、交互体和生物有机体的[[网络连通性]]这些重要概念<ref name="Rosen" /><ref>^ Heylighen, Francis (2008). "Complexity and Self-Organization". In Bates, Marcia J.; Maack, Mary Niles. Encyclopedia of Library and Information Sciences. CRC.</ref><ref>"abstract relational biology (ARB)". PlanetPhysics. Retrieved 2010-03-17.</ref>。近年来，人们把以信息论、网络拓扑/抽象图论概念为基础的两种互补方法在神经科学和人类认知等领域结合起来<ref name="springerlink" /><ref>http://hdl.handle.net/10101/npre.2011.6115.1 Wallace, Rodrick. When Spandrels Become Arches: Neural crosstalk and the evolution of consciousness. Available from Nature Precedings  (2011)</ref>。人们普遍认为，组织的复杂程度存在一种应与本体论的现实层次相区别层次结构<ref name="springerlink" /><ref>{{cite journal | author = Poli R | year = 2001a | title = The Basic Problem of the Theory of Levels of Reality | url = | journal = Axiomathes | volume = 12 | issue = 3–4| pages = 261–283 | doi = 10.1023/A:1015845217681 }}</ref><ref>{{cite journal | author = Poli R | year = 1998 | title = Levels | url = | journal = Axiomathes | volume = 9 | issue = 1–2| pages = 197–211 | doi=10.1007/bf02681712| pmid = 8053082 }}</ref>，现代等级分类的分类方法也承认生物圈的复杂层次结构，例如：生物领域和生物圈、生物的界、门、纲、目、科、属和种等。由于生物体具有动态性和组成的可变性、内在的“模糊性”、自生属性、自我繁殖的能力等等，生物体不符合一般系统的“标准”的定义，因此它们在功能和结构上都是“超级复杂”的；因此，在CSB中，生物体只能被定义为一种简单动态系统，“'''元系统'''”<ref name="springerlink" /><ref>[http://pespmc1.vub.ac.be/MST.html Metasystem Transition Theory], Valentin Turchin, Cliff Joslyn, 1993-1997</ref>。这样一个有机体、物种、“生态系统”等等的元系统定义 ,如自生系统理论中所述的系统的系统<ref>[http://archonic.net Reflexive Autopoietic Systems Theory]</ref>。它也不同于K.D. Palmer K·D·帕尔默在元系统工程中提出的定义<ref>[http://archonic.net/incosewg/ppframe.htm Meta-system Engineering], Kent D. Palmer, 1996</ref>，即生物体不同于具有固定输入输出转换函数的机器和自动机，或不同于具有固定相空间的连续[[动力系统]]<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A Framework for Systems with Dynamic Topology. ''International Journal of Computing Anticipatory System's'' 14:259–270</ref>，这与笛卡尔哲学思想相反；因此，尽管“非确定性自动机”和“模糊自动机”也被定义了，但生物体不能仅仅用状态、启动状态、输入和输出集/字母、转换函数五部分来定义<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A Framework for Systems with Dynamic Topology. ''International Journal of Computing Anticipatory System's'' 14:259–270</ref>。然而，棋盘自动机 tessellation automata或[[元胞自动机 cellular automata]] 提供了一种直观的、可视化的/计算的视角来洞察较低层次的复杂性，因此已经成为一种越来越流行的离散模型，研究领域包括可计算理论、应用数学、物理、计算机科学、理论生物学/系统生物学、癌症模拟和微观结构建模。利用[[遗传算法]]<ref>The Evolutionary Design of Collective Computation in Cellular Automata, James P. Crutchfeld, Melanie Mitchell, Rajarshi Das (In J. P. Crutchfield and P. K. Schuster (editors), Evolutionary Dynamics|Exploring the Interplay of Selection, Neutrality, Accident, and Function. New York: Oxford University Press, 2002.)</ref><ref>Evolving Cellular Automata with Genetic Algorithms: A Review of Recent Work, Melanie Mitchell, James P. Crutchfeld, Rajarshi Das (In Proceedings of the First International Conference on Evolutionary Computation and Its Applications (EvCA'96). Moscow, Russia: Russian Academy of Sciences, 1996.)</ref><ref>{{cite journal | doi = 10.1073/pnas.0307811100 | last1 = Peak | first1 = West | last2 = Messinger | first2 = Mott | year = 2004 | title = Evidence for complex, collective dynamics and emergent, distributed computation in plants | journal = Proceedings of the National Academy of Sciences of the USA | volume = 101 | issue = 4| pages = 918–922 |bibcode = 2004PNAS..101..918P | pmid = 14732685 | last3 = Messinger | first3 = SM | last4 = Mott | first4 = KA | pmc = 327117}}</ref> 实现[[元胞自动机]]是一个桥接棋盘自动机和CSB中的高层次复杂性方法之间差距的新兴领域。

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