摘要翻译：
复杂系统中的突现模式与现代科学和哲学中的许多有趣现象有关。弱涌现、强涌现和鲁棒涌现等几个概念被提出来强调问题的不同认识论和本体论方面。最重要的关注之一是，涌现是我们所观察到的现实的内在属性，还是认识论局限的结果。为了解释这个问题，我们通过构造拓扑提出了一个新的近似，一个允许我们将观察对象的空间（本体）与知识主体的概念装置（认识论）映射的框架。我们以一种特殊类型的突现过程为中心，即那些通过实验可以获得的过程，从这些过程中我们仍然没有关于产生其形成的机械过程的线索，我们分析了知识主体如何建立概念解释框架。在这些系统中，我们将概念析取识别为识别系统约束所需的关键逻辑操作。接下来，以一个三位合成系统为例，我们说明了约束的数量和范围是如何阻碍这种方案的发展的。有趣的是，我们发现我们的框架无法识别全局约束，无法将框架的认识论限制与系统的本体论特征清楚地联系起来。这允许我们提出一个涌现强度的定义，我们通过观察者对系统的积极干预使其与科学方法兼容。我们认为，这一定义调和了先前对突现过程进行分类的尝试，至少对于我们在此讨论的特定类型而言是如此。本文最后讨论了生物系统中的全局约束的相关性，它被理解为自然选择施加的向下因果影响。
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英文标题：
《A topological approach to the problem of emergence in complex systems》
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作者：
Alberto Pascual-Garc\'ia
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最新提交年份：
2016
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分类信息：

一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Physics        物理学
二级分类：Data Analysis, Statistics and Probability        数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  Emergent patterns in complex systems are related to many intriguing phenomena in modern science and philosophy. Several conceptions such as weak, strong and robust emergence have been proposed to emphasize different epistemological and ontological aspects of the problem. One of the most important concerns is whether emergence is an intrinsic property of the reality we observe, or it is rather a consequence of epistemological limitations. To elucidate this question, we propose a novel approximation through constructive topology, a framework that allow us to map the space of observed objects (ontology) with the knowledge subject conceptual apparatus (epistemology). Focusing in a particular type of emergent processes, namely those accessible through experiments and from which we have still no clue on the mechanistic processes yielding its formation, we analyse how a knowledge subject would build a conceptual explanatory framework. Working on these systems, we identify concept disjunction as a critical logical operation needed to identify the constraints of the system. Next, focusing on a three-bits synthetic system, we show how the number and scope of the constraints hinder the development of such scheme. Interestingly, we observe that our framework is unable to identify global constraints, clearly linking the epistemological limits of the framework with an ontological feature of the system. This allows us to propose a definition of emergence strength which we make compatible with the scientific method through the active intervention of the observer on the system. We think that this definition reconciles previous attempts to classify emergent processes, at least for the specific kind we discuss here. The paper finishes discussing the relevance of global constraints in biological systems, understood as a downward causal influence exerted by natural selection.
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PDF链接：
https://arxiv.org/pdf/1610.02448