复杂性科学视野下的广义进化论

将达尔文进化论的思想推广到分子进化和科学理论发展等领域,形成了可称之为广义进化论的研究。在美国心理学家和进化认识论创始人唐纳德.坎贝尔(Donald T.Campbell)提出的广义进化论原理的基础上,本文结合复杂性科学的研究,认为广义进化论的原理主要是:系统的盲目多样性与变异原理和系统的自组织与选择保存原理。广义进化论为物质系统、生命系统以及知识与社会系统的进化提供了一种新的整体论的研究进路。     

进化论的性质和结构

事实上,现代达尔文主义几乎统摄了现有的全部进化知识,综合进化论通常也被当作一个统一的理论。随着科学哲学思潮的演进和进化知识的进步,进化论科学与物理科学之间的巨大差别引起了科学哲学家的注意,进化论的性质和结构问题成了近三十年来西方生物学哲学中的一个争论焦点。显然,科学哲学家对此饶有兴味是同重新树立科学形象的目的相联系的,这是由于正统的科学哲学一直忽视生物科学而倾向于把物理学作为科学评价的标准。对进化论科学的注意,必将使我们对科学的理解更深刻、更全面。不过,这种讨论对进化论本     

进化论,一个错误的信仰

1859年,达尔文提出了进化论学说,他认为生物不是神创造的,而是经过漫长的岁月从简单到复杂进化来的。严格地说,进化论至今都只是一种假说,当年达尔文希望将来能发现确凿的证据,可是禁得起检验的证据至今也没有找到,而且进化论的理论与事实也出入太大,论证模棱两可,结论也无法重复。后来的学者是把进化论当作一种科学的信仰继承下来的。也正是因为信仰,才把它当成真理介绍给学术界和公众,这种新奇的假说很快形成了一个流行的信仰,人云亦云,被人们当成了真理。     

达尔文进化论对人类发展观念的深刻影响

达尔文进化论的诞生意义重大,其影响广泛且深远,特别是对人类发展观念的影响:达尔文进化论彻底动摇了"神创"世界的观念,在有机界确立起了发展的观念;达尔文进化论为人类的发展观念提供了科学支撑,坚定了人类对发展观念的信念,纠正了进步发展观念的主观主义倾向;与达尔文同时代的进化论学者斯宾塞将达尔文进化论的自然选择理论简单化为:物竞天择、适者生存,优胜劣败、强者为王等观念,即所谓弱肉强食的"丛林法则",并将其机械地照搬到人类社会领域,用其来说明人类社会的发展,其学说对人类的发展产生巨大的负面影响。     

达尔文进化论对人类发展观念的深刻影响

达尔文进化论的诞生意义重大,其影响广泛且深远,特别是对人类发展观念的影响:达尔文进化论彻底动摇了"神创"世界的观念,在有机界确立起了发展的观念;达尔文进化论为人类的发展观念提供了科学支撑,坚定了人类对发展观念的信念,纠正了进步发展观念的主观主义倾向;与达尔文同时代的进化论学者斯宾塞将达尔文进化论的自然选择理论简单化为:物竞天择、适者生存,优胜劣败、强者为王等观念,即所谓弱肉强食的"丛林法则",并将其机械地照搬到人类社会领域,用其来说明人类社会的发展,其学说对人类的发展产生巨大的负面影响。     

卡尔·波普的科学哲学对进化生物学的影响

卡尔·波普是为数不多的对科学界有重大影响的科学哲学家之一.但是,他从早期到晚年的关于进化生物学的言论严重阻碍了进化生物学的发展,他把进化论作为一个形而上学的研究纲领导致了许多科学家对进化论的误解,他否认进化定律的存在从而否认了进化生物学的科学地位.同时,我们指出了他关于进化论的新见解并没有任何新意.     

由花药主动运动导向直接完成的自花授粉机制——植物繁衍与生物进化的一种全新模式

多样性的生物种群与生态环境的相互作用、物种对环境演变的适应及其进化是恒久而常新的重大科学问题,而植物种群在其中扮演了举足轻重的角色。达尔文一百多年前曾对兰科等植物进行长期考察研究,发表了《兰花由昆虫授粉的各种巧妙方法》等许多著述,为生物进化论提供了重要依据。     

《进化论的结构——生命演化研究的方法论基础》一书出版

董国安教授所著《进化论的结构——生命演化研究的方法论基础》一书,已由人民出版社2011年7月出版。该书内容围绕进化论的科学地位及其与物理科学的关系等问题展开,对最近一个时期有关进化生物学哲学问题的争论进行了梳理。该书作者试图就进化论的结构和性质问题提出自己的解决方案。在回答是     

大家都来关心生物学的革命

十九世纪,细胞学说与达尔文进化论的建立使生物学从搜集和描述材料的科学,发展为实验科学;从分析、比较、整理材料的科学,发展为历史的科学。这是生物学的一次革命。二十世纪二十年代以来,量子力学的发展揭示了微观客体的运动规律。量子力学和大批     

达尔文学说在美国的命运

由于社会、经济和历史等方面的原因，达尔文进化论在美国生物学家、教师、公众以及联邦最高法院中近150年的经历，无庸置疑地证明，其作为生物发展规律的学说的传播并不是一项一蹴而就的事业，但是，随着科学技术和文化的进一步发展，接受进化论的人肯定会越来越多。     

Can Darwinian Mechanisms Make Novel Discoveries?: Learning from discoveries made by evolving neural networks

Some philosophers suggest that the development of scientificknowledge is a kind of Darwinian process. The process of discovery,however, is one problematic element of this analogy. I compare HerbertSimon's attempt to simulate scientific discovery in a computer programto recent connectionist models that were not designed for that purpose,but which provide useful cases to help evaluate this aspect of theanalogy. In contrast to the classic A.I. approach Simon used, ``neuralnetworks' contain no explicit protocols, but are generic learningsystems built on the model of the interconnections of neurons in thebrain. I describe two cases that take the connectionist approach a stepfurther by using genetic algorithms, a form of evolutionary computationthat explicitly models Darwinian mechanisms. These cases show thatDarwinian mechanisms can make novel discoveries of complex, previouslyunknown patterns. With some caveats, they lend support to evolutionaryepistemology.     

Evolution of Cognition: Towards the Theory of Origin of Human Logic

The main problem discussed in this paper is: “Why and how did animal cognition abilities arise?” It is argued that investigations of the evolution of animal cognition abilities are very important from an epistemological point of view. A new direction for interdisciplinary researches – the creation and development of the theory of human logic origin – is proposed. The approaches to the origination of such a theory (mathematical models of ``intelligent invention'' of biological evolution, the cybernetic schemes of evolutionary progress and purposeful adaptive behavior) as well as potential interdisciplinary links of the theory are described and analyzed.     

Lines of Descent: Kuhn and Beyond

Thomas S. Kuhn is famous both for his work on the Copernican Revolution and his ‘paradigm’ view of scientific revolutions. But Kuhn later abandoned the notion of paradigm (and related notions) in favour of a more ‘evolutionary’ view of the history of science. Kuhn’s position therefore moved closer to ‘continuity’ models of scientific progress, for instance ‘chain-of-reasoning’ models, originally championed by D. Shapere. The purpose of this paper is to contribute to the debate around Kuhn’s new ‘developmental’ view and to evaluate these competing models with reference to some major innovations in the history of cosmology, from Copernicanism to modern cosmology. This evaluation is made possible through some unexpected overlap between Kuhn’s earlier discontinuity model and various versions of the later continuity models. It is the thesis of this paper that the ‘chain-of-reasoning’ model accounts better for the cosmological evidence than both Kuhn’s early paradigm model and his later developmental view of the history of science.     

Greenhouse Effects in Global Warming based on Analogical Reasoning

Using an analogy in science and everyday life is a double-edged sword because they are accompanied by alternative ideas, in addition to scientific concepts. Schools and public education explain global warming by making a common analogy between this phenomenon and greenhouse effects (Chen in Philos Cogn Sci 105–114, 2012). Unfortunately, this analogy sometimes produces various incorrect explanatory mental models. To construct a correct understanding of global warming, it is necessary: first, to investigate the attributes of analogical reasoning; second, to understand these features by restructuring the greenhouse analogy; and third, to explore the problems and benefits of the greenhouse analogy. The characteristics of relations, rather than objects, must be mapped according to the principle of systematicity, but the public tends to preserve the attributes of the base domain, which is mapped relatively easily. In conclusion, certain facets of the prevailing greenhouse analogy cause a distorted public view of climate change. We must use the greenhouse analogy and yet simultaneously emphasize the relations and attributes highlighted and hidden in the analogy during evaluation.     

理论构成隐喻的指称

本文首先分析科学模型的隐喻性结构,从而引出隐喻词项的指称问题.接着以博义德对理论构成隐喻的指称功能的探讨为主线,分析出隐喻或模型要能隐喻地表达思想所预设的条件是:隐喻词项的隐喻性指称就是第一主概念表达式的所指,指称的固定则是靠第二主概念和第一主概念表达式涵义之间的类比进行的.最后表明理论构成隐喻作为一种以语言适应实在的策略,它的指称功能就在于为科学探究和理论构建提供认识论进路.     

兰伯特的几何学思想探析

德国数学家兰伯特在《平行线理论》中通过类比球面提出锐角假设在虚半径球面上成立,这一思想成为后来数学家建立和发展非欧几何的关键.兰伯特在对公理和定义的讨论中体现的几何哲学,使得他证明平行公设时回避了困扰前人的几何直观.他在同时期的数学工作中将圆函数和双曲函数类比,反映出其虚半径球面类比思想的来源和应用.     

对近代科学革命以前的科技关系的考察

近代以前的科学史不能看成单纯的科学思想史,把科学思想史与科技关系史结合起来考察,才能对古代科学、科学思想的特点以及它们的缓慢发展进行较合理的说明.     

Multiple Roles for Analogies in the Genesis of Fluid Mechanics: How Analogies Can Cooperate with Other Heuristic Strategies

When Johann and Daniel Bernoulli founded fluid dynamics they encountered several problems. To go beyond the vision of Newtonian particles, a new set of images was needed in order to deal with the spatial extensibility and lack of form of fluids. I point to evidence that analogy was an essential abductive strategy in the creation of this imagery. But its heuristic behavior is complex: analogy can provide an initial model or proto-model that establishes the starting point of a theoretical process, but it can play other roles as well. The historical genesis analyzed here shows that the participation of analogy in physicists’ creativity is not so restricted and that its richness opens up the field for very different roles and strategies in model-based discovery processes. Analogies can crop up intermittently in the evolution of a theory; and they can cooperate with images, extreme case reasoning and thought experiments, and even activate these processes at origin. Although it may seem that the contributions of analogy are generative in the sense of helping to discover new aspects of reality, we must stress the evaluative function that sometimes is performed by analogical reasoning in order to gain confidence. The study of the Bernoulli’s genesis of the foundations of fluid dynamics generates interesting hypotheses about the multiple roles that analogy can play in scientific model-based reasoning.     

Visual Models in Analogical Problem Solving

Visual analogy is believed to be important in human problem solving. Yet, there are few computational models of visual analogy. In this paper, we present a preliminary computational model of visual analogy in problem solving. The model is instantiated in a computer program, called Galatea, which uses a language for representing and transferring visual information called Privlan. We describe how the computational model can account for a small slice of a cognitive-historical analysis of Maxwell’s reasoning about electromagnetism.     

论科学理解的形成机制

在与科学说明的关系之比较中科学理解的概念、原理得以辨析清楚,其基本立场也在与一般理解概念的区别中得以凸显出来。其中判断力、逻辑力是形成科学理解的主要工具,类比是重要的机制,而陌生知识通过知识背景的整合从而丰富、改组原有知识结构是主要的过程。