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第480行：
第480行： − 克拉奇菲尔德认为任何系统的复杂性和组织性都是由观察者决定的主观品质。+ 第490行：
第490行： − 定义结构和探测自然界复杂性的出现本质上是主观的，尽管是必不可少的科学活动。尽管存在这些困难，这些问题可以从建模观察者如何从测量中推断出嵌入在非线性过程中的计算能力的角度进行分析。观察者对于什么是有序的，什么是随机的，什么是复杂的环境的概念直接取决于它的计算资源: 原始测量数据的数量，内存，以及可用于估计和推断的时间。发现环境中的结构更加关键和微妙地取决于这些资源是如何组织的。例如，观察者选择的(或隐含的)计算模型类的描述能力，可以是在数据中找到规律性的一个压倒性的决定因素。 裁判+ − 第626行：
第625行： − 另一方面，彼得 · 康宁认为: “难道协同作用必须被感知 / 观察，才能像某些理论家所说的那样，被称为突发效应吗？最明显的不是。与崛起相关的协同效应是真实的、可衡量的，即使没有人在那里观察它们。”+ 第642行：
第641行： − +
→主客的品质Objective or subjective quality
Crutchfield regards the properties of complexity and organization of any system as subjective qualities determined by the observer.
Crutchfield regards the properties of complexity and organization of any system as subjective qualities determined by the observer.
克拉奇菲尔德认为任何系统的复杂性和组织性都是由观察者的主观品质所决定的。
<blockquote>Defining structure and detecting the emergence of complexity in nature are inherently subjective, though essential, scientific activities. Despite the difficulties, these problems can be analysed in terms of how model-building observers infer from measurements the computational capabilities embedded in non-linear processes. An observer’s notion of what is ordered, what is random, and what is complex in its environment depends directly on its computational resources: the amount of raw measurement data, of memory, and of time available for estimation and inference. The discovery of structure in an environment depends more critically and subtly, though, on how those resources are organized. The descriptive power of the observer’s chosen (or implicit) computational model class, for example, can be an overwhelming determinant in finding regularity in data.<ref>
<blockquote>Defining structure and detecting the emergence of complexity in nature are inherently subjective, though essential, scientific activities. Despite the difficulties, these problems can be analysed in terms of how model-building observers infer from measurements the computational capabilities embedded in non-linear processes. An observer’s notion of what is ordered, what is random, and what is complex in its environment depends directly on its computational resources: the amount of raw measurement data, of memory, and of time available for estimation and inference. The discovery of structure in an environment depends more critically and subtly, though, on how those resources are organized. The descriptive power of the observer’s chosen (or implicit) computational model class, for example, can be an overwhelming determinant in finding regularity in data.<ref>
尽管是必不可少的科学活动，定义结构和探测自然界复杂性的出现本质上是主观的。尽管存在这些困难，这些问题可以从建模观察者如何从测量中推断出嵌入在非线性过程中的计算能力的角度进行分析。观察者对于什么是有序的，什么是随机的，什么是复杂的环境的概念直接取决于它的计算资源: 原始测量数据的数量，内存，以及可用于估计和推断的时间。发现环境中的结构更加关键性的和微妙地取决于这些资源是如何组织的。例如，观察者选择的(或隐含的)计算模型类的描述能力，可以是在数据中找到规律性的一个压倒性的决定因素。
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{{cite journal
On the other hand, Peter Corning argues: "Must the synergies be perceived/observed in order to qualify as emergent effects, as some theorists claim? Most emphatically not. The synergies associated with emergence are real and measurable, even if nobody is there to observe them."
On the other hand, Peter Corning argues: "Must the synergies be perceived/observed in order to qualify as emergent effects, as some theorists claim? Most emphatically not. The synergies associated with emergence are real and measurable, even if nobody is there to observe them."
另一方面，彼得·康宁认为: “难道协同作用必须被感知 / 观察，才能像某些理论家所说的那样，被称为涌现效应吗？最明显的不是。与涌现相关的协同效应是真实的、可衡量的，即使没有人在那里观察它们。”
See f.i. Carlo Rovelli: The mystery of time, 2017, part 10: Perspective, p.105-110
See f.i. Carlo Rovelli: The mystery of time, 2017, part 10: Perspective, p.105-110
请参阅详细资料。卡洛 · 罗维利: 时间之谜，2017年，第10部分: 透视，第105-110页
请参阅详细资料。卡洛 · 罗维利: 时间之谜，2017年，第10部分: 透视，第105-110页（这本书有中文资料）
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