专家系统工具中的推理技术

在基于规则的专家系统工具中，对于Ｒｅｔｅ模式匹配算法，有不同的实现方法．本文描述了一个新的证据生成算法，比较理想地实现了其思想．     

Conditional inference and advanced mathematical study

Many mathematicians and curriculum bodies have argued in favour of the theory of formal discipline: that studying advanced mathematics develops one’s ability to reason logically. In this paper we explore this view by directly comparing the inferences drawn from abstract conditional statements by advanced mathematics students and well-educated arts students. The mathematics students in the study were found to endorse fewer invalid conditional inferences than the arts students, but they did not endorse significantly more valid inferences. We establish that both groups tended to endorse more inferences which led to negated conclusions than inferences which led to affirmative conclusions (a phenomenon known as the negative conclusion effect). In contrast, however, we demonstrate that, unlike the arts students, the mathematics students did not exhibit the affirmative premise effect: the tendency to endorse more inferences with affirmative premises than with negated premises. We speculate that this latter result may be due to an increased ability for successful mathematics students to be able to ‘see through’ opaque representations. Overall, our data are consistent with a version of the formal discipline view. However, there are important caveats; in particular, we demonstrate that there is no simplistic relationship between the study of advanced mathematics and conditional inference behaviour.

论经验思维--自然语言基本思维方式系列研究之一

经验思维是遵循直观同异对立统一律、运用经验思维方法操作经验语词代换、把握对象观念 ,建构用经验逻辑结构起来的思维成果的逻辑规律型代换思维。直观同异对立统一律是在不变革对象观念的前提下 ,从直观的同与异的对立统一中径直地把握、代换对象观念的逻辑规律。经验逻辑是通过经验思维组织经验逻辑形式而建构起来的思维成果之意义的结构。经验逻辑形式是经验思维成果之意义结构的一般模式 ;包括经验概念、经验命题、经验推理、经验论证等。经验思维是人类历史上创造的第一个运用自然语言的基本思维方式。运用经验思维 ,人类创造了辉煌的古代文化。它的历史功绩应充分肯定 ,它的否定也是必然的     

论回溯推理的命题形式

回溯推理的一般逻辑形式为 ( q→ ( p→ q) )→ p。为了更有效地应用回溯推理 ,增加回溯推理的实用价值 ,丰富回溯推理在逻辑形式上的变化 ,笔者着重论述了回溯推理的一些具体形式 ,并且分析出这些具体形式的逻辑特性。回溯推理的具体形式有 :联言式、选言式、假言式等     

Measurement Invariance Testing with Many Groups: A Comparison of Five Approaches

With the increasing use of international survey data especially in cross-cultural and multinational studies, establishing measurement invariance (MI) across a large number of groups in a study is essential. Testing MI over many groups is methodologically challenging, however. We identified 5 methods for MI testing across many groups (multiple group confirmatory factor analysis, multilevel confirmatory factor analysis, multilevel factor mixture modeling, Bayesian approximate MI testing, and alignment optimization) and explicated the similarities and differences of these approaches in terms of their conceptual models and statistical procedures. A Monte Carlo study was conducted to investigate the efficacy of the 5 methods in detecting measurement noninvariance across many groups using various fit criteria. Generally, the 5 methods showed reasonable performance in identifying the level of invariance if an appropriate fit criterion was used (e.g., Bayesian information criteron with multilevel factor mixture modeling). Finally, general guidelines in selecting an appropriate method are provided.     

关联理论在日语听力教学中的应用探讨

关联理论是语用学的一个分支,是研究信息交际过程中的推理过程和话语解释原则的理论。关联理论在日语听力教学中的应用,应当注重推理训练和日本生活图式的培养,丰富学生的“百科知识”和“逻辑知识”。作者从日本语能力测试1级听力教学材料和教学实践入手,总结了日语听力课学生容易出现的语境把握不充分和图式缺乏等问题,并提出了强化话轮相邻对的语用推理教学和加强日本生活图式教学等解决方案。     

Accounting for Model Uncertainty in the Prediction of University Graduation Rates

Empirical analysis requires researchers to choose which variables to use as controls in their models. Theory should dictate this choice, yet often in social science there are several theories that may suggest the inclusion or exclusion of certain variables as controls. The result of this is that researchers may use different variables in their models and come to disparate conclusions with respect to predicted effects and their statistical significance. In such cases one is uncertain of which particular set of regressors forms the model that represents the data. The approach used below accounts for uncertainty in variable selection by using Bayesian model averaging (BMA). Accounting for uncertainty, we demonstrate that BMA provides better out-of-sample prediction for university graduation rates than results based on alternative variable selection methods.     

自发特质推理研究的回顾与展望

自发特质雅理是指个体在没有特定目的甚至在完全没有意识到的情况下，根据他人的行为信息推论其人格特质、形成印象的过程。国外对自发特质推理现象的理论解释有直觉模型和过程模型，用语义启动和图形启动两种范型加以研究，结果显示，知觉者的练习、年龄、意识目的、人格特点及被知觉者的特点都会影响自发特质推理。自发特质推理的研究在人格评价、职业面试等方面有广阔的应用前景。     

语用推理与话语的理解

语用学旨在解释听话人如何理解话语的意图。格赖斯和斯波伯及威尔逊都主张靠语用推理。但是格赖斯的会话含义理论是从社交语用角度出发，建立在合作原则基础上的推理；斯波伯及威尔逊是从认知角度出发，以大脑中的演绎为基础的推理。本通过分析这两大不同的语用推理模式，使我们更好理解话语。并且，通过对比指出他们各自的不足，以促使后来学积极探讨这个课题。     

模糊控制技术发展及其应用

模糊控制是智能控制的一个重要分支,在过去十年中得到了广泛的应用。简要回顾模糊控制技术诞生和发展的历史,介绍了模糊控制技术的特点,特别是模糊控制的结构和工作原理以及模糊控制技术的最新发展,总结模糊控制技术近年来的应用。