科学建模的两种观点

关于科学建模有两种典型的观点,一是"系统派生观",二是"零碎借贷观"。前者认为,科学表征模型可以在原理模型(即科学原理)的基础上系统派生出来;后者强调科学家的科学建模活动实际上是从各种理论中选取所需要的部分进行创造性构造的过程。从以往的争论来看,这两种观点似乎各有侧重,不分胜负。但本文试图结合科学建模的案例论证,后者完全可以替代前者,不仅因为它比前者更符合科学家实际的建模活动,解释前者无法解释的现象,而且可以容纳理论派生模型的案例。     

中国国家创新系统政策议程设置过程研究

中国国家创新系统的结构一直存在"创新孤岛",本文应用多源流理论与Dolowitz-Marsh政策移植模型,通过分析该政策的议程设置过程,从政策制定源头查找问题的成因。通过解析问题溪流,明确政策移植的目的;通过梳理政治溪流,发现关键行为者;通过追溯政策溪流,探究政策移植的内容、程度与来源。在此基础上,试图厘清促进多源流聚合并打开政策窗口的因素,发现政策移植在政策议程设置中的作用,以及该方式并未解决决策权碎片化与部门利益固化问题的缺陷。     

结构同构与科学表征

科学模型究竟如何表征它们的目标系统,哲学界目前尚未达成共识。理论的语义观曾长期支配着人们对科学理论和模型的理解。一些哲学家认为,其中的结构主义或许能为我们提供一种科学表征理论。不过,仔细研究会发现科学表征不能根据模型和目标系统之间的同构关系获得解释,结构同构观并不是一种可行方案。模型包含结构,但科学表征不能还原为结构表征。科学表征依赖于对目标系统具体的信息描述,并且与实际的推理功能紧密关联。     

自我欺骗问题研究——意向论vs.非意向论

关于自我欺骗的道德心理学理论主要分为意向论和非意向论两大阵营。以戴维森为首的意向论阵营强调自欺是一种意向行为,按照一种人际间欺骗模型来认识自欺。意向论者认为人的心灵可以分为不同的人格系统,试图用一种非理性的心理因果性来解释自欺。以梅勒为首的非意向论者反对人际间欺骗模型,从而也反对把自欺看作一种意向行为,梅勒试图将自欺与认知心理学对接,认为自欺是由人类的认知特点造成的,而不是人自主造成的。梅勒提出偏差信念论之后,英美学界对自欺的讨论进入了一个新的阶段,但是这些新的观点又各有各的问题。我们将看到,引入不同的自我知识的理论能够帮助完善以上各个理论,为解决它们的问题提供帮助。     

可持续发展的哲学阐释与计算方法

可持续发展的哲学内涵是人地关系的协调与地球系统的平衡。协调论强调“1 1>2”的非线性的螺旋式发展,平衡论强调既稳定又不稳定的混沌边界的协调度。地球系统(自然界系统、人类系统)作为复杂巨系统,应采用“从定性到定量综合集成研讨厅体系”方法,计算协调度(cm)与可持续发展临界值(Q),从而建立地球模型,真正实现可持续发展。本文以整体哲学与混沌理论对可持续发展进行了全新的阐释,试图以协调论与平衡论建立地球系统的可持续发展模型。     

知觉二元论:二元化的另一种方式

从隐私论题出发,本文将精神事件定义为从内在的观点所得到的知觉,把物理事件定义为从外在的观点所得到的知觉,并以此为起点发展出一个关于心灵的知觉二元论。本文还试图以此理论来说明心灵哲学领域长期存在的心-物互动问题,试图恢复并证明笛卡尔和莱布尼兹曾经达到的某些观察和结论。知觉是心灵最本质的特征,本文在用知觉来定义精神事件和物理事件的同时也发展出一个关于知觉的新理论。     

遗传算法之父——霍兰及其科学工作

霍兰是遗传算法发明人。他在复杂性系统科学方面提出复杂自适应系统(CAS)理论;他提出的涌现性理论对于组织知识创新具有重要意义。本文试图对霍兰的学术背景、简历、在遗传算法、CAS理论、涌现性方面的奠基性工作加以详细研究和评述,并评价霍兰在遗传算法、复杂性系统科学上的奠基性地位。     

意向立场与目的论立场的关系

意向立场和目的论立场是我们对能动者行为进行解读时所采取的不同解释模式,对这两者之间关系的讨论至今还未达成共识。本文首先介绍了目前关于这一问题的两种主要理论:即目的论立场起源于意向立场以及意向立场是目的论立场发展的延伸;其次分析和讨论了这两种理论各自的解释困难;最后文章进一步对这两种立场的关系问题提出了新的观点,即主要通过分析婴儿对欲念/目标、信念和意向这些心灵状态的理解,以及来自相关的脑神经科学实验结果的支持,试图说明基于欲念/目标的目的论立场与更为复杂的掌握信念、意向和语言之后的意向立场有着各自不同的起源机制,是两套独立的行为认知系统。     

从复杂系统理论看智能设计论

本文在对智能设计论兴起的科学依据进行方法论分析的基础上,着重从复杂系统理论的角度,探讨了与智能设计相关的两个主要问题,即偶然性和不可还原性.通过科学和哲学上的论证,试图表明,尽管进化论等在细节上还有很多不足,但智能设计论也并不因此成为目前科学条件下惟一合理的理论选项.     

拉卡托斯的划界标准能解决科学与伪科学之间的划界问题吗?

本文试图论证拉卡托斯对波普尔科学划界的理解是有偏差的,以及他的进步性标准并不能成功地解决科学与伪科学的划界问题。波普尔试图区分的是科学与伪科学。尽管拉卡托斯声称自己也试图解决这一科学划界问题,但是他的论证以及他提出的进步性标准都将历史上那些曾经构成科学的理论(可称为"不再使用的科学"或"过时的科学")与伪科学置于同等地位,这显然是有失偏颇的。     

Theory of Knowledge in System Dynamics Models

Having entered into the problem structuring methods, system dynamics (SD) is an approach, among systems’ methodologies, which claims to recognize the main structures of socio-economic behaviors. However, the concern for building or discovering strong philosophical underpinnings of SD, undoubtedly playing an important role in the modeling process, is a long-standing issue, in a way that there is a considerable debate about the assumptions or the philosophical foundations of it. In this paper, with a new perspective, we have explored theory of knowledge in SD models and found strange similarities between classic epistemological concepts such as justification and truth, and the mechanism of obtaining knowledge in SD models. In this regard, we have discussed related theories of epistemology and based on this analysis, have suggested some implications for moderating common problems in the modeling process of SD. Furthermore, this research could be considered a reword of system dynamics modeling principles in terms of theory of knowledge.     

Philosophical Issues and their Implications for the Systems Architect

Many system architects select their system methodologies without explicit consideration of the philosophical perspectives that impact their decisions. This paper describes how the concepts of ontology and epistemology apply in systems science. Ontology is how we specify terms of reference for existence, allowing us to understand the theory of existence via an ‘existence framework’. Epistemology, the theory of knowledge, allows us to explore new models and theories of knowledge acquisition so the best system-based methodologies can be deployed to solve complex system problems. After introducing these concepts, the paper presents system science issues and assesses the impact of ontological, axiological and epistemological perspectives on system methodology selection, research, system design and deployment. An ontological viewpoint such as realism, as an objective view is contrasted versus nationalism, a personal perceptional view. An epistemological viewpoint is explored comparing knowledge as a product of sensory perception or rational reflection. The paper’s significant contribution is that it helps system architects understand that their philosophical views of systems science impact their system methodology choices.     

多团队系统理论及其在现代企业管理中的应用

多团队系统理论是一种超出对以往单个团队研究,并将其作为组织活动系统一部分的团队研究中独立出来的新视角和研究方法,以多维度、多水平、多目标结构层次模型来观察企业团队的行为方式,是团队理论研究的创新趋势。本文从多团队的领导关系、多团队与复杂系统及多团队与产品研发等方面对近年来有关多团队的研究成果进行了综述,并就该理论在现代企业多团队组建、多团队协作运营及企业多团队领导中的应用进行了初步探讨。最后,对MTS理论的研究前景进行了展望,并提出了在企业管理应用中存在的问题。     

A Theory of Scientific Model Construction: <Emphasis Type="Italic">The Conceptual Process of Abstraction and Concretisation</Emphasis>

The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, we select position and momentum and establish a relation amongst the two variables, which we call Newton’s 2nd law. The specification of the unspecified elements of scientific laws, e.g. the force function in Newton’s 2nd law, is what would establish the link between the assertions of the theory and physical systems. In order to unravel how and with what conceptual resources scientific models are constructed, how they function and how they relate to theory, we need a view of theory-application that can accommodate our constructions of representation models. For this we need to expand our understanding of the process of abstraction to also explicate the process of specifying force functions etc. This is the second principal level at which abstraction enters in our theorising and in which I focus. In this paper, I attempt to elaborate a general analysis of the process of abstraction and concretisation involved in scientific- model construction, and argue why it provides an explication of the construction of models of the nuclear structure.     

绿蓝问题与简单性方案

绿蓝问题是假说选择问题的一种范型.科学假说精确的逻辑结构应该包含假说适用的情景和敏感因子.简单性标准是广为接受的一种假说选择标准,在运用到解决绿蓝问题时,提出了简单性的句法理论和语义理论.但这两种理论分别遭遇了对表达系统和概念框架的相对性,不能处理某些绿蓝型问题,甚至会陷入反直观境地的难题.     

Emergence,Computation and the Freedom Degree Loss Information Principle in Complex Systems

We consider processes of emergence within the conceptual framework of the Information Loss principle and the concepts of (1) systems conserving information; (2) systems compressing information; and (3) systems amplifying information. We deal with the supposed incompatibility between emergence and computability tout-court. We distinguish between computational emergence, when computation acquires properties, and emergent computation, when computation emerges as a property. The focus is on emergence processes occurring within computational processes. Violations of Turing-computability such as non-explicitness and incompleteness are intended to represent partially the properties of phenomenological emergence, such as logical openness, given by the observer’s cognitive role; structural dynamics where change regards rules rather than only values; and multi-modelling where multiple non-equivalent models are required to model such structural dynamics. In this way, we validate, from an epistemological viewpoint, models and simulations of phenomenological emergence where the sequence of events constitutes the natural, analogical non-Turing computation which a cognitive complex system can reproduce through learning. Reproducibility through learning is different from Turing-like computational iteration. This paper aims to open a new, non-reductionist understanding of the conceptual relationship between emergence and computability.     

复杂系统的隐喻描述与模型描述

由隐喻描述走向模型描述是复杂性科学成熟的标志.本文重点介绍了复杂系统的两种模型描述方法:形式化系统模型与关联论模型,并比较它们各自的优缺点.两种模型是从不同的角度对复杂系统的描述,在复杂系统的理论研究与实际运用中都有着重要的、不可替代的意义.复杂系统的未来研究方向并不是对于两种模型的"整合",而是两种模型交替并用,以多元视角科学地揭示复杂系统的本质.     

社会计算——科学、技术与人文的数字化动态交融

本文通过社会计算的研究,探讨了科学、技术和人文有机组合的途径。主要内容是讨论如何利用复杂系统理论及先进的计算手段和方法,把传统上限于语言层次和静态的人文知识数字化和动态化,并用于各种复杂社会问题的建模、分析和决策支持。主要思想包括利用人工系统、计算试验和平行系统等方法,建立社会计算的理论框架。     

复杂性探索与控制论发展

复杂性探索催生了控制论发展,而控制论发展又促进了复杂性探索,二者相互促进,共同发展.从复杂性探索的角度来看,以维纳为代表的传统控制论既有其历史贡献,也有其历史局限性.感知控制论和元系统跃迁理论,作为一种系统进化控制论,发展和超越了传统控制论,为研究复杂系统及其进化问题提供了一个独到的视角,成为当今复杂性探索控制论转向的重要标志.     

Metric Models for Random Graphs

Many problems entail the analysis of data that are independent and identically distributed random graphs. Useful inference requires flexible probability models for such random graphs; these models should have interpretable location and scale parameters, and support the establishment of confidence regions, maximum likelihood estimates, goodness-of-fit tests, Bayesian inference, and an appropriate analogue of linear model theory. Banks and Carley (1994) develop a simple probability model and sketch some analyses; this paper extends that work so that analysts are able to choose models that reflect application-specific metrics on the set of graphs. The strategy applies to graphs, directed graphs, hypergraphs, and trees, and often extends to objects in countable metric spaces.