创造的"模板"

所谓“模板”是一种隐喻的说法，人们往往相信，创造需要给予完全的自由，只要突破任何框架的约束，就能增加产生创意的概率。然而，被告诫“打破规则”的人，并不一定比那些遵循规则的人更善于解决问题，因为，一个可供参考的认知框架将会增强人们对“游戏规则”的敏感度，基于模板的创意具有高度的创造性。选择力是隐藏于创造性背后的“忽略的智慧”。科学发现是模式识别与选择性搜索的协作过程，如何从“信息海洋”里捞出那根真正有意义的“针”，也许能从意向性中找到答案。另一方面，过量的信息导致了注意力的贫乏，在信息化社会的今天，注意力成为稀缺的资源。当新信息潮水般涌来的时候，如果没有将它有秩序地纳入意识，精神错乱就容易出现。创造性思想的形成同时伴随着思维的混沌，在这关键时刻出现的无序正是精神分裂的表现。而思维中的有序性和条理性是一种对混沌控制的结果，它来自思维中的自组织和不同层次间的相互调控。     

论豪森对无奇迹论证的反驳与推进

作为实在论辩护的核心策略之一,无奇迹论证试图从科学的经验性成功推论其"近似真理性",并以"无奇迹"作为置信度指标。豪森分析了无奇迹论证的基本逻辑,批评了其在"近似真理"概念上的问题与逻辑困境,并通过揭示论证过程中的基础概率谬误否定了其逻辑有效性。随后,通过引入主观概率解释以及"休谟不等式",豪森提出了一个逻辑上有效的无奇迹论证形式。在贝叶斯主义的框架下,该论证保证了一定的客观性,且与实在论辩护的"局域化"策略殊途同归,从而为实在论提供了较为合理的辩护。     

切比雪夫的概率思想及其数学文化背景

切比雪夫不等式和切比雪夫大数定律是概率论极限理论的基础,其创立是概率论成为严密数学分支的标志.大多有关研究成果都侧重于切比雪夫及其后继者的贡献,本文将重点考察切比雪夫概率思想的创新点及其数学文化背景,尤其是法国数学文化对切比雪夫概率思想形成的深刻影响.另外,还探讨了切比雪夫不等式优先发现权问题.     

在计算机中创造生命可能吗?——兼评《数字创世纪——人工生命的新科学》

人工生命的重要思想,作为在计算机媒介中的生命系统,人工生命在生命如其所能(Life-as-it-could-be)的广阔内容下,考察生命系统所可能的存在形式。如其所能的生命是现实生命系统的一种隐喻和类比,研究不同系统中的相似性才是人工生命核心的理念。人工生命与现实生命都是生命存在的一种形式,但缺少一个统一的生命理论框架,自创生则是上世纪70年代发展起来的用于认识生命系统“活”性的理论,本文将其引入到人工生命中,以期实现各种生命形式的统一。     

吉利斯的概率哲学理论述评

英国哲学家吉利斯的主要研究领域为概率基础、逻辑哲学与数学哲学,对概率哲学的学习和研究至今已有四十余年。在吉利斯关于概率哲学的研究中,他对当今各种主要的概率解释都给予过深刻的检视。他对这些概率解释所面临的困难的讨论使他得出了自己关于概率这个概念的相当具有原创性的见解。本文试图勾勒出吉利斯的概率哲学理论的一个基本轮廓,并对其中的一些观点给予分析和评价。     

军语概念体系的框架编制原则

军语概念体系的框架编制是军语编纂工作中的一个重要基础环节,应主要把握科学性、实用性、特色性、创新性、规范性的原则,以确保框架分类合理、特色鲜明、操作便利。     

评波普尔对归纳问题的取消

波普尔认为,科学知识即理论内容的增长是科学进步的最为重要的标志。然而,科学理论的内容丰富程度与逻辑概率之间正好是反变关系,因此,科学的目标不是追求理论的高概率,而是追求理论的低概率,不是追求理论的可证实性,而是追求理论的可证伪性。既然归纳推理是确立结论真实性或概然性的推理,所以,归纳推理是与科学目标背道而驰的,因而应当将它从科学方法论中清除出去,相应地,休谟提出的归纳问题也就一并被取消了。然而,当波普尔引入“逼真性”概念以后,他的验证方法便不可能是完全演绎的,或多或少地含有归纳的成分。因此,波普尔对归纳问题的取消是不成功的。     

伦理推理:一种中国古代归纳推理——以儒、墨两家为例

中国"推类"逻辑的归纳特性剖析表明,中国古代有归纳逻辑,作为一种非形式逻辑,其推理类型具有不同于西方归纳逻辑的特殊性,具体体现在推类的价值相关性上。从逻辑系统看,伦理推理是中国古代归纳逻辑的基本推理系统。儒墨对丧礼的不同推论表明,伦理推理具有三个特征:大前提有较强语境敏感性;推导一般不具演绎有效性,更具概率性;类比是推论的主要方式。虽然在伦理推理中可以找到作为公理的基本伦理原则,但是采取概率逻辑的视角,人们的主观概率有时候并不遵循外延性原则,这为伦理推理中的非外延性或情境等内涵因素提供了一种合理性辩护。     

基于"术语在线"的科技术语多义表征研究——以航空和航海术语为例

文章以“术语在线”为主要验证平台,以全国科学技术名词审定委员会发布的权威词库为基准语料,对航空与航海相关领域的若干典型交叉词条的义项进行了对比分析,并就其语义框架与阐释空间进行研究。研究发现:首先,在航空与航海领域存在大量的同形同义、同形异义和同义异形现象。其次,此类术语的语义表征依赖于特定的联立关系,受到相应概念元素的规约。一方面,在其依存的具体语义框架内,其语义表征符合单义性原则;另一方面,在学科交叉背景下,该类术语具备明显的学科间性特征,其语义表征具有多义阐释空间。     

奥斯特罗格拉茨基的概率思想探赜

奥斯特罗格拉茨基是圣彼得堡概率学派的杰出代表,其对相关实际问题的应用研究推动了概率论在俄罗斯的传播和发展。他坚持认为概率论是数学分析最重要的应用分支之一:为天文学提供了大量基本数学观察方法,可确定比数学观察误差影响还要小的随机事件原因等,其社会服务功能刺激了诸如保险业等社会福利机构的产生和发展,进而促进了自然科学的相关理论发展。由于深受拉普拉斯概率思想之影响,奥斯特罗格拉茨基虽然把概率论看作研究随机现象规律的有力工具,但经常犯一些哲学观和方法论错误。     

Default Priors for Neural Network Classification

Feedforward neural networks are a popular tool for classification, offering a method for fully flexible modeling. This paper looks at the underlying probability model, so as to understand statistically what is going on in order to facilitate an intelligent choice of prior for a fully Bayesian analysis. The parameters turn out to be difficult or impossible to interpret, and yet a coherent prior requires a quantification of this inherent uncertainty. Several approaches are discussed, including flat priors, Jeffreys priors and reference priors.     

Applications of quantum statistics in psychological studies of decision processes

We present a new approach to the old problem of how to incorporate the role of the observer in statistics. We show classical probability theory to be inadequate for this task and take refuge in the epsilon-model, which is the only model known to us caapble of handling situations between quantum and classical statistics. An example is worked out and some problems are discussed as to the new viewpoint that emanates from our approach.Supported by the I UAP-III no. 9.     

Contemporary Epistemic Logic and the Lockean Thesis

This paper studies the Lockean thesis from the perspective of contemporary epistemic logic. The Lockean thesis states that belief can be defined as ‘sufficiently high degree of belief’. Its main problem is that it gives rise to a notion of belief which is not closed under conjunction. This problem is typical for classical epistemic logic: it is single-agent and static. I argue that from the perspective of contemporary epistemic logic, the Lockean thesis fares much better. I briefly mention that it can successfully be extended from single-agent to multi-agent settings. More importantly, I show that accepting the Lockean thesis (and a more sophisticated version for conditional beliefs) leads to a significant and unexpected unification in the dynamic behavior of (conditional) belief and high (conditional) probability with respect to public announcements. This constitutes a methodological argument in favor of the Lockean thesis. Furthermore, if one accepts Baltag’s Erlangen program for epistemology, this technical observation has even stronger philosophical implications: because belief and high probability display the same dynamic behavior, it is plausible that they are indeed one and the same epistemic notion.     

Bloc Voting in the United States Senate

blocs and legislative measures are partitioned into types so that, as nearly as possible, votes by each bloc for each type of measure are either all YEAs or all NAYs. A probability model is given for the partitions into blocs and types, and for the pattern of YEAs and NAYs given the partitions. The Alternating Randomized Combination algorithm is presented for searching for high probability partition pairs. The probability of each bloc and type in the final optimal partition pair is estimated by Markov Chain Monte Carlo. The final partition identifies 18 blocs of Senators, and 14 types of legislative measures. The blocs and types are delineated in a table reporting all decisive votes in the 103rd Congress. The blocs are characterized by the types of measures in which they vote against the majority party.     

框架语义学视角下航空英语半技术词一词多义现象及汉译策略探究

半技术词(semi-technical word)或次技术词(sub-technical word)是科技文体中应用最广的词,有学者认为,科学思想和技术内容的展开主要依靠半技术词来实现。在航空领域,英语半技术词汇呈现出体量大、词频高、跨学科、多义性、语义负荷低等语用特征。尽管多数半技术词汇没有形成严格的体系,但其词义往往取决于专业内容和词的联立关系,这种联立关系即行业背景下的语义框架。对于航空英语半技术词汇中普遍存在的一词多义现象,可以运用框架语义学的视角加以描述阐释,为译者术语知识体系的建构提供认知基础,进而为此类术语的翻译决策过程提供行之有效的策略。     

A Probability for Classification Based on the Dirichlet Process Mixture Model

In this paper we provide an explicit probability distribution for classification purposes when observations are viewed on the real line and classifications are to be based on numerical orderings. The classification model is derived from a Bayesian nonparametric mixture of Dirichlet process model; with some modifications. The resulting approach then more closely resembles a classical hierarchical grouping rule in that it depends on sums of squares of neighboring values. The proposed probability model for classification relies on a numerical procedure based on a reversible Markov chain Monte Carlo (MCMC) algorithm for determining the probabilities. Some numerical illustrations comparing with alternative ideas for classification are provided.     

Estimation and Prediction for Stochastic Blockmodels for Graphs with Latent Block Structure

a posteriori blockmodeling for graphs is proposed. The model assumes that the vertices of the graph are partitioned into two unknown blocks and that the probability of an edge between two vertices depends only on the blocks to which they belong. Statistical procedures are derived for estimating the probabilities of edges and for predicting the block structure from observations of the edge pattern only. ML estimators can be computed using the EM algorithm, but this strategy is practical only for small graphs. A Bayesian estimator, based on the Gibbs sampling, is proposed. This estimator is practical also for large graphs. When ML estimators are used, the block structure can be predicted based on predictive likelihood. When Gibbs sampling is used, the block structure can be predicted from posterior predictive probabilities. A side result is that when the number of vertices tends to infinity while the probabilities remain constant, the block structure can be recovered correctly with probability tending to 1.     

术语能力培养中的理论问题

术语理论发展经历过两个大的转向,首先是描述转向,然后是认知转向。描述转向使得术语学朝着实际应用的方向发展,因而成为能够对术语能力培养实践进行指导的理论基础。认知术语理论则强调了术语资源的分布性。在这种分布性下,术语能力可以视为在不同知识表征之间进行切换的能力。分布式认知理论为这种能力的培养提供了理论框架和培养路径。     

A Framework Linking Non-Living and Living Systems: Classification of Persistence, Survival and Evolution Transitions

We propose a framework for analyzing the development, operation and failure to survive of all things, living, non-living or organized groupings. This framework is a sequence of developments that improve survival capability. Framework processes range from origination of any entity/system, to the development of increased survival capability and development of life-forms and organizations that use intelligence. This work deals with a series of developmental changes that arise from the uncovering of emergent properties. The framework is intended to be general, but we see a potential to apply it to scientific topics such as the exploration of the origin of life or the search for life beyond Earth, and to understand some biological issues in evolution and symbiosis, and also to apply to social systems that do not seem to be operating well, to determine their problems and correct them.

拉普拉斯概率论的衰落

作为概率论历史中一个重要发展阶段的拉普拉斯概率论在20世纪初期走到了它的尽头。从19世纪初开始的关于概率论在法律判决中应用的争论、柯西的“新数学”的兴起及其对最小二乘法的责难、对拉普拉斯概率论基础的批评以及公理化概率论的产生等四个方面的讨论,展示了拉普拉斯概率论衰落的历史轮廓。