特征归纳的关联相似性模型

作者提出特征归纳的关联相似性模型,用以描述以归纳特征的关联特征相似性为基础的归纳推理,把归纳推理中相似性和关联知识统一整合起来。该模型认为归纳强度主要取决于归纳特征与关联特征的关联强度和关联特征的相似性程度的乘积,归纳信心主要取决于关联强度,从而分离归纳信心和归纳强度。以大学生为被试的两个实验的主要结果支持关联相似性模型的主要预测。关联相似性模型能够描述解释以关联特征相似性为基础的归纳推理现象,比以往的归纳理论具有更大的解释能力和解释范围     

归纳推理中相似性和类别标签的作用

该文采用“篇章阅读”实验范式探索了归纳推理中前提类别和结论类别间相似性、结论类别标签属性对归纳推理的作用。90名大学生被试参加了3个实验。实验1结果表明,归纳推理受前提类别和结论类别之间相似性的影响,相似性越高归纳推理力度越强;实验2结果表明,归纳推理还受结论类别上位类别知识的影响,当类别属性和相似性冲突情况下,被试更倾向按照类别属性进行推理;实验3结果表明,归纳推理通达上位类别知识是一个主动建构的过程,即使是在类别标签不确定的情况下,被试仍然依赖类别标签进行推理。并初步提出了“归纳推理力度=两事物相似性×归类概率”模型设想。     

特征相似性、类别标签与因果关系在归纳推理中的作用

采用人工材料,比较类别标签、特征相似性与因果关系对归纳推理强度的影响。包括两个实验,实验1比较类别标签与特征相似性对归纳推理的影响,结果表明,当类别标签对归纳推理的影响显著强于特征相似性时,不能将类别标签等同于一个相似性特征。实验2进一步探讨类别标签与因果关系对归纳推理的作用,结果表明,因果关系作用明显强于类别标签的作用。综合两个实验的结果并整合前人相关研究,提出了不同关系影响归纳推理的强度假想。     

归纳推理的抽样理论

作者提出归纳推理的抽样理论,认为归纳推理实质是根据与归纳特征有关的抽样样本情况来推断结论类别具有归纳特征的可能性,其中的抽样可分为类别抽样和特征抽样两种。以大学生为被试的两个实验结果一致支持抽样理论而不是别的归纳推理理论。对于归纳推理的主要现象,抽样理论比其它的相似性解释具有更大的解释范围,特别是能够解释其它理论严格不能解释的归纳推理非对称性现象     

基于概率的归纳推理模型

归纳推理是指从个别前提推出一般结论的推理,它是人的一项基本认知能力,也是心理学研究需要解释的重要现象.在模拟归纳推理时,不能排除先验知识对归纳推理结论力度的影响,贝叶斯理论可以结合条件对先验概率进行修正,能够很好地将先验知识引入到归纳推理中来.文章重点介绍了基于记忆的贝叶斯模型,相似性概率模型和结构统计模型对归纳推理的解释.     

归纳推理中的属性中心性效应

通过三个实验研究了属性的中心性程度对归纳推理的影响,结果表明,在归纳推理中存在属性中心性效应,中心属性比其他属性（次中心属性、再次中心属性）更能影响归纳推理。但属性中心性效应的出现受到了前提对象和结论对象相似性程度的制约,当前提对象和结论对象的相似程度高时,中心属性比其他属性更能影响归纳推理;随着相似性水平的降低,中心属性的归纳推理力度越来越弱,而次中心属性、再次中心属性的归纳推理力度则会依次表现出越来越强的趋势,到最后当前提对象和结论对象的属性完全不相似时,最次中心属性的归纳推理力度达到最高水平,而中心属性的归纳推理力度则降低到最低水平。由于再次中心属性的归纳推理力度的最高水平没有显著高于随机水平,而中心属性的归纳推理力度的最低水平却显著低于随机水平,因此,研究者认为,在前提对象和结论对象完全不相似的情况下,被试将确信不能采用中心属性来进行归纳推理的力度判断,而采用猜测的方式选择了肯定可以排除的项目之外的其他项目,这体现了具有不确定的归纳推理活动的过程的典型特征     

对归纳推理非对称性现象的特征迁移解释

作者创新提出对归纳推理非对称性现象的特征迁移解释,认为根据由前提类别已知的特征集合构成的特征样本中迁移出现在结论类别中的特征的比例,能预测作为新特征的归纳特征由前提类别迁移到结论类别的可能性。以大学生为被试的实验结果支持对非对称性现象的特征迁移解释而不是原来的两种相似性解释。     

特征相似性和因果解释在归纳推理中的整合

为探讨特征相似性和因果解释在个体归纳推理中的作用,在控制知识经验影响的前提下,设置了非决定性的因果关系,操纵了因果机制强度和前提与结论对象之间的特征相似性水平,结果发现:(1)实验1结果显示,相似性和因果解释在归纳推理中的效应均显著,相似性效应随因果解释强度的减弱而增强,相似性与因果解释的相互作用影响归纳推理。(2)实验2结果显示,当基于相似性推论与基于因果解释推论产生冲突时,相似性和因果解释在归纳推理中的效应均显著,二者的交互作用不显著。在强、弱两种因果解释条件下,相似性在归纳推理中的效应均非常显著。总的结果表明特征相似性与因果解释共同影响个体的归纳推理,人们会整合两种信息进行归纳推理。     

配对刺激的结构对相似性判断非对称性的影响

笔者考察一个被先前相似性研究忽略的问题:配对刺激的结构对有方向相似性判断的非对称性的可能影响。实验被试是大学生。实验自变量是人工概念配对的特征结构,有三种实验条件:对齐且对称结构、非对齐且对称结构和非对齐且不对称结构。结果发现,在对齐且对称结构条件和非对齐且对称结构条件下没有出现相似性判断的非对称现象,在非对齐且不对称结构条件下出现相似性判断的非对称现象。相似性判断是否出现非对称性取决于配对刺激的结构是否非对称,而不受配对刺激的结构是否对齐的影响。这支持相似性判断的特征对比模型在αβ时的预测,而不支持Tversky原初主张αβ时特征对比模型的预测,也不支持量子相似性模型的预测。     

颜色、形状和大小相似性与变化性对儿童归纳推理的影响

设计了两个实验任务,探讨了颜色、大小和形状对68名8～10岁儿童归纳推理的影响。结果发现,在相似性任务中,当测试图片分别与两组前提图片在大小和形状(颜色)上一致时,儿童认为测试图形与大小一致图形具有相同属性;当测试图片分别与前提图片在形状和颜色上一致时,儿童倾向于选择形状一致图形具有的属性。在变化性任务中,当两组前提图片分别在大小和形状上变化,而测试图形与前提组图形不同时,儿童认为测试图形与大小变化图形具有相同属性;当两组前提图片分别在颜色和大小(形状)上变化时,儿童的选择没有显著差异;这一结果与同时变化每组前提图片的两个特征差异不显著,表明单独变化颜色、大小和形状来构成推理任务是比较合理的。     

特征归纳中关联强度与关联相似性的交互作用效应

根据特征归纳的关联相似性模型分析和三个因素实验研究发现,在基于关联相似性而进行的特征归纳中,关联强度和关联相似性两因素对归纳强度的影响存在交互作用效应。关联相似性变化对归纳强度的影响依赖于关联强度,随关联强度的增加而增加。关联强度变化对归纳强度的影响依赖于关联相似性水平：在高的关联相似性条件下,归纳强度随关联强度增加而增加;在中等关联相似性条件下,归纳强度不受关联强度变化的影响;而在低的关联相似性条件下,归纳强度随关联强度增加而减小     

A relevance theory of induction

A framework theory, organized around the principle of relevance, is proposed for category-based reasoning. According to the relevance principle, people assume that premises are informative with respect to conclusions. This idea leads to the prediction that people will use causal scenarios and property reinforcement strategies in inductive reasoning. These predictions are contrasted with both existing models and normative logic. Judgments of argument strength were gathered in three different countries, and the results showed the importance of both causal scenarios and property reinforcement in categorybased inferences. The relation between the relevance framework and existing models of category-based inductive reasoning is discussed in the light of these findings.     

The role of causal models in analogical inference

Computational models of analogy have assumed that the strength of an inductive inference about the target is based directly on similarity of the analogs and in particular on shared higher order relations. In contrast, work in philosophy of science suggests that analogical inference is also guided by causal models of the source and target. In 3 experiments, the authors explored the possibility that people may use causal models to assess the strength of analogical inferences. Experiments 1-2 showed that reducing analogical overlap by eliminating a shared causal relation (a preventive cause present in the source) from the target increased inductive strength even though it decreased similarity of the analogs. These findings were extended in Experiment 3 to cross-domain analogical inferences based on correspondences between higher order causal relations. Analogical inference appears to be mediated by building and then running a causal model. The implications of the present findings for theories of both analogy and causal inference are discussed.     

It's a sign of the kind: gestures and words guide infants' inductive inferences

The role of words and gestures in guiding infants' inductive inferences about nonobvious properties was examined. One hundred seventy-two 14-month-olds and 22-month-olds were presented with novel target objects followed by test objects that varied in similarity to the target. Objects were introduced with a novel word or a novel gesture or with no label. When target and test objects were highly similar in shape, both 14- and 22-month-olds inferred that these objects shared a nonobvious property, regardless of whether the objects were labeled with a word or a gesture or with no label. When objects were labeled with the same word, both 14- and 22-month-olds generalized the nonobvious properties to objects that shared minimal perceptual similarity. Finally, when objects were labeled with the same gesture, 14-month-olds, but not 22-month-olds, generalized the nonobvious properties to objects that shared minimal perceptual similarity. These results indicate that 14-month-olds possess a more generalized symbolic system as they will rely on both words and gestures to guide their inferences. By 22-months of age, infants treat words as a privileged referential form when making inductive inferences.     

Non‐Bayesian Noun Generalization in 3‐ to 5‐Year‐Old Children: Probing the Role of Prior Knowledge in the Suspicious Coincidence Effect

It is unclear how children learn labels for multiple overlapping categories such as “Labrador,” “dog,” and “animal.” Xu and Tenenbaum (2007a) suggested that learners infer correct meanings with the help of Bayesian inference. They instantiated these claims in a Bayesian model, which they tested with preschoolers and adults. Here, we report data testing a developmental prediction of the Bayesian model—that more knowledge should lead to narrower category inferences when presented with multiple subordinate exemplars. Two experiments did not support this prediction. Children with more category knowledge showed broader generalization when presented with multiple subordinate exemplars, compared to less knowledgeable children and adults. This implies a U‐shaped developmental trend. The Bayesian model was not able to account for these data, even with inputs that reflected the similarity judgments of children. We discuss implications for the Bayesian model, including a combined Bayesian/morphological knowledge account that could explain the demonstrated U‐shaped trend.     

主题关系在4~5岁儿童不同属性归纳推理发展中的作用

为探讨主题关系在儿童归纳推理中的作用,采用经典的三角归纳范式,设计了主题关系和知觉相似冲突、主题关系和分类学关系冲突两种情形,来考察4~5岁儿童在内在属性和情境性属性任务中的归纳推理。结果显示：当主题关系和知觉相似冲突时,从4.5岁开始儿童主要基于主题关系对情境性属性进行归纳推理,而对于内在属性的推论,4~5岁儿童在基于主题关系和基于知觉相似上没有显著差异。当主题关系和分类学关系冲突时,从4.5岁开始儿童主要基于主题关系对情境性属性进行归纳推理,从5岁开始儿童主要基于分类学关系对内在属性进行归纳推理。两个实验结果均发现5岁和5.5岁儿童能够依据不同的属性使用不同的关系推理,表现出归纳灵活性     

Relations between premise similarity and inductive strength

According to the diversity principle, diverse evidence is strong evidence. There has been considerable evidence that people respect this principle in inductive reasoning. However, exceptions may be particularly informative. Medin, Coley, Storms, and Hayes (2003) introduced a relevance theory of inductive reasoning and used this theory to predict exceptions, including the nondiversity-by-propertyreinforcement effect. A new experiment in which this phenomenon was investigated is reported here. Subjects made inductive strength judgments and similarity judgments for stimuli from Medin et al. (2003). The inductive strength judgments showed the same pattern as that in Medin et al. (2003); however, the similarity judgments suggested that the pattern should be interpreted as a diversity effect, rather than as a nondiversity effect. It is concluded that the evidence regarding the predicted nondiversity-byproperty-reinforcement effect does not give distinctive support for relevance theory, although this theory does address other results.     

P3b反映基于相似性的图形类别归纳决策过程(309)

先前关于归纳推理的研究没有探讨过图形类别归纳任务中决策过程的事件相关电位(ERPs)特征。该研究采用图形材料,通过记录和分析图形类别归纳推理任务的结论评估阶段的脑电信号,探讨了不同类别条件下图形归纳推理决策过程的ERP特征。实验结果显示,推理决策过程中,当前提为一些狗具有某种属性特征时,结论一致类别(狗类及马类)比结论不一致类别下(椅子类)的归纳推理诱发了更大的P3b的波幅; 而结论一致类别下,类别内(狗类)比类别外(马类)推理诱发更大的后部脑区的P3b的波幅,反映了相似性对类别归纳的贡献。该研究为理解类别归纳过程的决策阶段的动态加工过程提供了神经电生理学证据。研究结果进一步支持了类别归纳的相似性理论模型。