Supporting the formal verification of mathematical texts

The formal verification of mathematical texts is one of the most interesting applications for computer systems. In fact, we argue that the expert language of mathematics is the natural choice for achieving efficient mathematician–machine interaction. Our empirical approach, the analysis of carefully authored textbook proofs, forces us to focus on the language and the reasoning pattern that mathematician use when presenting proofs to colleagues and students. Enabling a machine to understand and follow such language and argumentation is seen to be the key to usable and acceptable math assistant systems. In this paper, we first perform an analysis of three textbook proofs by hand; we then describe a computational framework that aims at mechanising such an analysis. The resulting proof-of-concept implementation is capable of processing simple textbook proofs and constitutes promising steps towards a natural mathematician–machine interface for proof development and verification.     

幼儿反事实推理的错误源分析

本研究选取57名3~5岁幼儿,考察了在两种选择和三种选择的反事实推理任务中儿童的表现以及是否出现现实错误。结果如下:无论在两种还是三种选择的反事实任务中,3岁组儿童的得分显著低于4岁和5岁组儿童,而4岁和5岁组儿童之间不存在显著差异;幼儿在反事实推理中的确会出现现实错误,但除此之外,幼儿在三种选择任务中也会选择现实和正确答案之外的第三个选项。由此可见,年幼儿童可能在抑制现实和建构反事实替代情境方面都存在困难,这尚需我们进一步探究。     

Distortion of probability and outcome information in risky decisions

Substantial evidence indicates that information is distorted during decision making, but very few studies have assessed the distortion of probability and outcome information in risky decisions. In two studies involving six binary decisions (e.g., banning blood donations from people who have visited England, because of “mad cow disease”), student and nonstudent participants distorted their evaluations of probability and outcome information in the direction of their preferred decision alternative and used these biased evaluations to update their preferences. Participants also evaluated the utilities of possible outcomes more positively when the outcomes could follow only from the preferred alternative and more negatively when they could follow only from the competing alternative. Such circular reasoning is antithetical to the normative consequentialist principles underlying decision analysis. Presenting numerical information as precise values or as ranges of values did not significantly affect information distortion, apparently because the manipulation did not affect perceived ambiguity as intended.     

A causal model theory of the meaning of cause, enable, and prevent

The verbs cause , enable , and prevent express beliefs about the way the world works. We offer a theory of their meaning in terms of the structure of those beliefs expressed using qualitative properties of causal models, a graphical framework for representing causal structure. We propose that these verbs refer to a causal model relevant to a discourse and that "A causes B" expresses the belief that the causal model includes a link from A to B. "A enables/allows B" entails that the model includes a link from A to B, that A represents a category of events necessary for B, and that an alternative cause of B exists. "A prevents B" entails that the model includes a link from A to B and that A reduces the likelihood of B. This theory is able to account for the results of four experiments as well as a variety of existing data on human reasoning.     

The development of possibility judgment within and across domains

The ability to differentiate possible events from impossible ones is an invaluable skill when reasoning about claims that transcend the perceptual evidence at hand, yet preschool-aged children do not readily make this differentiation when reasoning about physically extraordinary events [Shtulman, A., &; Carey, S. (2007). Improbable or impossible? How children reason about the possibility of extraordinary claims. Child Development, 78, 1015–1032]. The present study sought to determine whether this failure stems from deficits in domain-specific knowledge or deficits in the domain-general procedure by which possibility judgments are made. Participants (48 children aged 4-9 years olds and 16 adults) were asked to judge the possibility of three types of extraordinary events – physical, psychological, and biological – and to justify their judgments of impossibility. Developmental changes in the ability to differentiate improbable events from impossible events were qualitatively similar across domains. Moreover, participants’ propensity to judge improbable events possible was significantly correlated with the quality of their justifications, both within and across domains. These findings suggest that modal development involves a domain-general change in how modal claims are evaluated.     

Evaluating Dialectical Structures

This paper develops concepts and procedures for the evaluation of complex debates. They provide means for answering such questions as whether a thesis has to be considered as proven or disproven in a debate or who carries a burden of proof. While being based on classical logic, this framework represents an (argument-based) approach to non-monotonic, or defeasible reasoning. Debates are analysed as dialectical structures, i.e. argumentation systems with an attack- as well as a support-relationship. The recursive status assignment over the arguments is conditionalised on proponents in a debate. The problem of multiple status assignments arising on circular structures is solved by showing that uniqueness can be guaranteed qua reconstruction of a debate. The notion of burden of proof as well as other discursive aims rational proponents pursue in a debate is defined within the framework.     

基于非逻辑机制的条件推理模式：P—Q映射模型及其实证检验

研究结合数学分析方法,提出了基于非逻辑机制的条件推理模型：P-Q映射模型。并根据这个模型,对人们在不同命题类型奈件下的推理行为进行了预测。预测结果显示,当推理前提为LH和HL型命题时,基于P-Q映射模型的预测结果与基于条件概率模型的预测结果完全一致。但当推理前提为LL和HH型命题时,两种模型给出的预测结果存在差异。实验结果表明,当前提命题为LL和HH型命题时,被试的条件推理行为与P-Q映射模型的预言完全一致。     

关系推理中信念偏差效应的研究

采用结论评估范式,考察时向和空间关系推理中信念偏差效应的表现形式,以及心理模型理论对关系推理中信念偏差效应的解释力。研究结果表明,关系推理中信念偏差效应的表现形式与三段论有所不同,不论是时间推理还是空间推理中都存在信念主效应,但没有发现信念与逻辑的交互作用;心理模型理论不能对关系推理中信念偏差效应作出合理解释。     

对归纳推理贝叶斯模型的检验

作者用实验比较检验特征归纳的贝叶斯模型、关联相似性模型、基于特征的归纳推理模型和相似性覆盖模型这四种模型。以大学生为被试的实验结果表明：1）在强关联强度一致时,被试的归纳推理基本符合贝叶斯模型和关联相似性模型的预测,在弱关联强度一致时,不符合这四种模型预测;2）在关联强度不一致时,关联强度效应不符合贝叶斯模型的预测;3）在关联强度一致时,贝叶斯模型和关联相似性模型的预测结果是一致的,不能区分两个模型。实验结果较多地支持贝叶斯模型和关联相似性模型。