直言推理系统

本文构造了直言推理的一个系统MA,内容包括直接推理和三段论,但未考虑单称命题。此系统实际上是名辞逻辑系统MZ的子系统,精确地说是关于类名及其否定和由它们形成的本辞的系统。文中证明了系统MA的可靠性和完全性,并提出了它的自然推理系统。     

Commentary: Are There Good Reasons to Adopt Dynamic Systems Approaches for Explaining Deductive Reasoning?

The focus of this commentary is twofold. First, I examine Faiciuc’s attempts to counter symbolic computationalism as a major theoretical framework for the study of deductive reasoning. Second, I wish to see how far the author goes in her defense of Dynamic Systems Approaches (DSAs) as a more promising framework for explaining logical reasoning. When reading her work, I posed two versions of the same for/against question to myself: How strong is the case against symbolic computationalism? And, on the basis of the author’s argumentation, would one feel justified in adopting DSAs instead? I examine each question in turn, and come to similar conclusions. The article by Faiciuc tackles issues of relevance to any serious effort toward reflecting on the two perspectives being compared. Unfortunately, however, references to studies supporting her claims are rather thin. A better-informed answer to the question raised in the title of the article is still to be given.     

Are there Reasons to Challenge a Symbolic Computationalist Approach in Explaining Deductive Reasoning?

The majority of the existing theories explaining deductive reasoning could be included in a classic computationalist approach of the cognitive processes. In fact, deductive reasoning could be seen to be the pinnacle of the symbolic computationalism, its last fortress to be defended in the face of new, dynamic, and ecological perspectives over cognition. But are there weak points in that position regarding deductive reasoning? What would be the reasons for which new perspectives could gain in credibility? What could be their most important tenets? The answers given to those questions in the paper include two main points. The first one is that the present empirical data could not sustain unambiguously one view over the other, that they are obtained in artificial experimental conditions, and that there are data that are not easily explainable using the traditional computationalist paradigm. The second one is that approaching the deductive reasoning from dynamic and ecological perspectives could have significant advantages. The most obvious one is the possibility to integrate more easily the research regarding the deductive reasoning with the results obtained in other domains of the psychology (especially in what respects the lower cognitive processes), in artificial intelligence or in neurophysiology. The reasons for that would be that such perspectives, as they are sketched in the paper, would imply, essentially, processes of second-order pattern formation and recognition (as it is the case for perception), embodied cognition, and dynamic processes as the brain ones are.     

Everyday Life Reasoning, Possible Worlds and Cultural Processes

Discussing Faiciuc’s paper, I first tackle the problem of fallacies in deductive reasoning showing how, in a possible world theory, non correct forms of reasoning can be useful strategies for discovery, providing these strategies remain at a hypothesis level. Secondly, everyday reasoning and its specificity in comparison to logical-normative one are analyzed. This topic stresses the notion of interpretation and, in this context, the role of the community and of cultural canons shared by the subject. From this point of view, reasoning does not occur, only, in the brain of a person but in everyday exchanges occurring between individuals and the history of their community.

从知觉分心任务看儿童类比推理能力的发展

采用四类图片类比映射任务,考察了知觉分心对90名4岁、5岁、6岁儿童类比推理能力发展的影响,并进一步阐释影响儿童类比推理能力发展的可能机制。四类图片类比映射任务分别为一种关系无分心任务、一种关系有分心任务、两种关系无分心任务和两种关系有分心任务。结果表明：（1）在具备相应知识经验的前提下,知觉分心对儿童类比推理成绩有显著影响,儿童在无分心任务中的表现明显好于知觉分心任务的表现。在无分心条件下,4岁儿童已经开始能够选择关系匹配来正确完成类比推理。错误分析发现知觉分心任务中儿童所犯错误主要是分心错误,而且分心错误随年龄增长呈下降趋势。这表明对知觉分心的抑制控制可能是儿童类比推理能力发展的一个重要影响因素。（2）随着年龄增长,儿童类比推理能力逐渐提高。总体表现为6岁组的成绩显著优于4岁、5岁组的成绩,而4岁组的成绩与5岁组的成绩没有显著差异。5岁可能是儿童能够抑制知觉分心进行类比推理的快速发展期     

推理与决策的双加工理论研究简评

决策与推理的双加工理论是一个颇有影响力的理论,通过对两个加工系统的基本特点、区别点以及基本关系、推理错误原因等几个方面进行分析阐述,发现目前在该理论的一些基本问题的认识上还存在诸多问题。主要表现在以下几方面：（1）两个加工系统的关键区别点不在于工作记忆有无绝对参与;（2）对于推理和决策错误的原因,不同的双加工理论给出了不一致的解释;（3）今后有待从情绪与推理决策的关系、影响等方面加深对推理与决策错误的理解     

3～5岁儿童表面与结构相似性类比推理的实验研究

采用经典类比推理问题对3~5岁儿童表面相似性与结构相似性类比推理能力进行了实验研究。结果发现:(1)表面相似性与结构相似性对儿童解决类比问题的影响不同。一般来说,前者更有利于3~5岁儿童类比问题的解决;(2)儿童解决表面相似性与结构相似性类比问题的能力随年龄增长而发展,但发展趋势不同。在表面相似性问题方面,4岁以前发展较慢,而4岁以后的发展较快;在结构相似性问题方面,4岁以前发展较快,而4岁以后的发展较慢。4岁是儿童解决类比推理问题能力的转折点;(3)在本实验条件下,工作记忆负荷对儿童解决表面相似性类比问题与结构相似性类比问题的影响不显著;(4)类比映射关系提示能促进儿童解决两类类比问题,但对不同年龄儿童的作用是非线性的。     

A re-investigating of the religious orientation-moral reasoning relationship: a relational developmental systems perspective

This study re-investigates the relationship between religious orientation and Kohlberg’s moral reasoning among students at a midwestern (USA) university. Multiple regression analyses revealed that quest-oriented religiosity was significantly positively related to principled moral reasoning, as consistently found in previous studies, while intrinsic religious orientation showed no relation to principled moral reasoning. We discuss our findings through a lens of relational developmental systems theory, suggesting that a more integrative measure is needed to better understand the complex relationship between religious orientation and moral reasoning.     

“如果P,那么Q,……?”─—儿童充分条件假言演绎推理能力发展初探

以日常生活事件为内容的三套测验题探查了9－15岁儿童充分条件假言推理能力的发展。研究发现被试有关能力的发展可以区分出三种不同水平；儿童对充分条件假言推理规则的掌握没有固定的难易顺序，这取决于课题任务的性质和主体思维发展水平。研究还探查了发展的个体内部差异和个体之间的差异以及影响差异的各种内外因素。     

Incorporating Demographic Embeddings Into Language Understanding

Meaning depends on context. This applies in obvious cases like deictics or sarcasm as well as more subtle situations like framing or persuasion. One key aspect of this is the identity of the participants in an interaction. Our interpretation of an utterance shifts based on a variety of factors, including personal history, background knowledge, and our relationship to the source. While obviously an incomplete model of individual differences, demographic factors provide a useful starting point and allow us to capture some of this variance. However, the relevance of specific demographic factors varies between situations—where age might be the key factor in one context, ideology might dominate in another. To address this challenge, we introduce a method for combining demographics and context into situated demographic embeddings—mapping representations into a continuous geometric space appropriate for the given domain, showing the resulting representations to be functional and interpretable. We further demonstrate how to make use of related external data so as to apply this approach in low‐resource situations. Finally, we show how these representations can be incorporated into improve modeling of real‐world natural language understanding tasks, improving model performance and helping with issues of data sparsity.