因果强度推理的贝叶斯模型综述

因果强度推理的贝叶斯模型以因果协变关系、贝叶斯定理和因果图形模型为基础,借助蒙特卡洛算法实现模型对被试因果强度估计的预测。通过选用不同的先验分布、似然函数、蒙特卡洛取样方法和基于后验分布的预测方法,因果强度推理的贝叶斯模型可以精确预测很多以往模型不能解释的实验结果,并对被试的推理过程提出有价值的见解,还可推广到对因果结构判断的预测和对多原因(结果)交互作用的解释;但需要在如何选择先验分布和似然函数、解释被试如何表征与作答、扩大单个模型解释范围和简化计算等方面继续完善。     

记叙文中因果连贯对空间情境模型回溯建构的促进

采用移动窗口阅读技术探讨记叙文理解中因果关系对于空间信息加工的作用。实验1和2的自变量是故事中空间信息与故事结果的因果关系,采用相关样本t检验对不同条件下探测词的反应时进行统计分析,结果表明因果关系不仅会影响文本明确提及的空间信息的加工而且能够促进隐含的空间关系建构情境模型。实验3的自变量是故事中物体与位置词的空间关系,采用相关样本t检验对不同条件下位置探测词的反应时进行统计分析,结果进一步表明空间情境模型是读者为保持故事因果连贯回溯建构的而不是在阅读进程中的实时建构。实验4中空间关系的复杂程度增大,结果发现当故事中空间信息的文本距离较远时即使有保持因果连贯的需要,读者仍无法回溯建构空间模型。     

预测特征竞争范式下的特征推理方式

当面临归类不确定的情景时,人们的特征推理是基于类别进行,还是基于特征联结进行,一直是类别研究中的重要内容。本研究采用预测特征竞争范式对这一问题进行了探究。共两个实验：实验1采用预测特征竞争范式探讨推理前预先归类时,人们的推理方式是基于类别还是基于特征联结。实验2采用预测特征竞争范式探讨推理前不预先归类时,人们的推理是基于类别还是基于特征联结。实验结果表明,推理前预先归类时,被试倾向于基于类别进行推理。推理前不预先归类时,被试倾向于根据特征联结进行推理。     

基于认知诊断的被试类比推理测验行为分析

本文在构建被试解题路径模型的基础上,应用多策略多成分潜在特质模型研究被试类比推理测验的行为,精细地分析了被试在类比推理过程中所使用的策略、分析了影响被试类比推理测验策略选择的因素、估计了被试在类比推理测验中所表现的各种能力.     

因果信息和提示指导语对大学生贝叶斯推理的影响

基于三重加工心智模型,以大学生为被试,采用经典贝叶斯推理的文本范式,通过操纵自变量：因果信息（有或无）与提示指导语（提供或不提供）,试图探讨激发反省心智,消解理性障碍的情况下,因果贝叶斯框架的作用机制。估计正确率和准确性的结果都表明因果信息显著提高了贝叶斯推理成绩,准确性的结果也说明指导语可以提示被试放下既有观念,以无偏见的方式进行推理,从而有效促进了贝叶斯推理表现。而在提示条件下增加因果信息并没有促进作用,表明对于较高元认知的被试因果信息作用是有限的。     

因果信息和提示指导语对大学生贝叶斯推理的影响

基于三重加工心智模型，以大学生为被试，采用经典贝叶斯推理的文本范式，通过操纵自变量：因果信息（有或无）与提示指导语（提供或不提供），试图探讨激发反省心智，消解理性障碍的情况下，因果贝叶斯框架的作用机制。估计正确率和准确性的结果都表明因果信息显著提高了贝叶斯推理成绩，准确性的结果也说明指导语可以提示被试放下既有观念，以无偏见的方式进行推理，从而有效促进了贝叶斯推理表现。而在提示条件下增加因果信息并没有促进作用，表明对于较高元认知的被试因果信息作用是有限的。     

因果变化模式与因果联结强度在幼儿因果推理中的作用

对93名幼儿进行了五种因果变化模式的因果推理题目的测试。结果表明:(1)在不同的因果变化模式下,被试进行因果推理的成绩存在差异,且在对于这五类题目的掌握上具有一定的顺序。(2)被试在同样因果变化模式题目的表现之间具有较高的相似性,而在因果联结强度相同的题目之间则具有显著的差异。(3)被试对于各题目回答的正确率并不随原因与结果联结次数的增多而提高。(4)即使是在观察到的刺激完全一致的情况下,被试的回答仍会因因果变化模式的差异及主试对于题目解释的不同而存在差别。     

归类不确定时特征推理的单类说理论

人们不能完全确定某个事物应该归入哪个类别的情境,被称作“归类不确定的情境”。关于归类不确定情境中的特征推理,目前有两种理论解释：Anderson的理性模型和Murphy与Ross的“单类说”。理性模型认为,在归类不确定情境中,预测事物是否具有某个特征时,人们会考虑该事物可能属于的所有类别,既会考虑靶类别的信息,又会考虑非靶类别的信息。单类说则相反,认为在归类不确定情境下的特征推理,人们只会考虑靶类别的信息,而不考虑非靶类别的信息。该文重点介绍了单类说的发展进程,并对归类不确定情境中的特征推理进行了展望     

小学儿童两维空间方位传递性推理能力的发展

研究了小学儿童两维空间方位传递性推理能力的发展水平及认知策略,同时,对心理模型理论进行了检验。被试为城市中等小学7岁、9岁、11岁儿童各24名,男女各半。单模型和双模型两种实验任务均为四前提。采用个别实验,儿童在前提呈现的情况下进行推理。主要研究结果：（1）7岁儿童开始萌发了两维空间方位传递性推理能力,9岁儿童和11岁儿童的推理能力处于发展和提高过程中;（2）随着年龄增长,使用模型建构策略解决问题的儿童人次越来越多,绝大部分11岁儿童都能使用这一策略进行推理。但即使儿童使用了模型建构策略,他们的推理成绩也没有反映出模型数量所造成的任务难度差异,即不符合心理模型理论关于模型数量的主要预期;（3）即使儿童能自发生成模型建构策略,儿童在两维空间方位传递性推理中使用这一策略的有效性程度并不高。     

任务情境和证据信息对青少年贝叶斯推理的影响研究

采用生活情境测查任务和经典测查任务探讨了任务情境对青少年贝叶斯推理的影响,以及生活情境测查任务中不同证据信息对青少年贝叶斯判断的影响作用.结果表明:(1)在生活情境测查任务中,从小学六年级到大学二年级,被试的贝叶斯推理能力稳步缓慢提升(相邻的两个被试组之间差异不显著,而不相邻的两个被试组之间差异更容易达到显著水平),发展没有出现加速期,而经典测查任务情境下没有表现出年龄差异;(2)贝叶斯推理作为条件概率的判断不仅受任务情境的影响,而且同一任务情境中不同证据信息也会影响贝叶斯判断.当证据信息与先验信念一致时,被试可以充分利用线索进行推理.     

The conceptual centrality of causal cycles

How do causal cycles affect judgments of conceptual centrality? Generally, a feature is central to a concept to the extent that other features in the concept depend on it, thereby rendering it immutable from the concept (Sloman, Love, &; Ahn, 1998). Previous research on conceptual centrality has focused primarily on features involved in four major types of dependency structures: simple cause-effect relations, causal chains, common-cause structures, and common-effect structures. Causal cycles are a fifth type of dependency structure commonly reported in people’s real-life concepts, yet to date, they have been relatively ignored in research on conceptual centrality. The results of six experiments suggest that previously held assumptions about the conceptual representation of cycles are incorrect. We discuss the implications of these findings for our understanding of theory-based concepts.     

Effect of causal structure on category construction

In four experiments, the question of how the causal structure of features affects the creation of new categories was examined. Features of exemplars to be sorted were related in a single causal chain (causal chain), were caused by the same factor (common cause), or caused the same effect (common effect). The results showed that people are more likely to rely on common-cause or common-effect background knowledge than on causal-chain background knowledge in category construction. Such preferences suggest that the common-cause or the common-effect structures are considered more natural conceptual structures.     

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.     

Finding similarity in a model of relational reasoning

Similarity plays a central role in the study of perception and cognition. Previous attempts to model similarity have captured effects of either featural or structural similarity, but typically not both. We simulated both by fitting similarity data with the LISA model of relational reasoning [Hummel, J. E., & Holyoak, K. J. (1997). Distributed representations of structure: A theory of analogical access and mapping. Psychological Review, 104, 427–466, Hummel, J. E., & Holyoak, K. J. (2003a). A symbolic-connectionist theory of relational inference and generalization. Psychological Review, 110, 220–264]. The same mechanisms LISA uses to simulate analogy also provide a natural account of feature-based similarity effects (e.g., violations of symmetry), structural effects (e.g., the advantage of alignable over non-alignable differences), and the combined effects of featural and structured information (i.e., MIPs and MOPs; “Matches In/Out of Place”) on similarity judgments. Our approach differs from most models of similarity in that LISA was not originally designed to simulate similarity judgments, but rather analogical reasoning. LISA’s incidental ability to simulate diverse similarity effects speaks to the plausibility of the model’s account of human knowledge representation.     

Structural constraints and object similarity in analogical mapping and inference

Theories of analogical reasoning have viewed relational structure as the dominant determinant of analogical mapping and inference, while assigning lesser importance to similarity between individual objects. An experiment is reported in which these two sources of constraints on analogy are placed in competition under conditions of high relational complexity. Results demonstrate equal importance for relational structure and object similarity, both in analogical mapping and in inference generation. The human data were successfully simulated using a computational analogy model (LISA) that treats both relational correspondences and object similarity as soft constraints that operate within a limited-capacity working memory; but not with a model (SME) that treats relational structure as pre-eminent.     

推理方向与规则维度对儿童因果推理的影响

采用Frye和Zelazo等（1996）所设计的“二进二出”装置（斜面滚球装置）,设置了不同的推理方向、规则维度的因果推理任务,采用个别实验法,研究了60名3.5～4.5岁儿童因果推理能力的发展。结果发现：（1）儿童在不同方向的因果推理任务上成绩差异显著,因→果推理成绩要好于果→因推理;（2）不同维度下儿童的推理成绩有极显著的差异性,一维的因果推理更容易,三维合取规则的因果推理任务更难;（3）3.5～4岁左右是儿童因果推理能力发展的快速期。     

A computational account of children's analogical reasoning: balancing inhibitory control in working memory and relational representation

Theories accounting for the development of analogical reasoning tend to emphasize either the centrality of relational knowledge accretion or changes in information processing capability. Simulations in LISA (Hummel & Holyoak, 1997, 2003), a neurally inspired computer model of analogical reasoning, allow us to explore how these factors may collaboratively contribute to the development of analogy in young children. Simulations explain systematic variations in United States and Hong Kong children's performance on analogies between familiar scenes (Richland, Morrison & Holyoak, 2006; Richland, Chang, Morrison & Au, 2010). Specifically, changes in inhibition levels in the model's working-memory system explain the developmental progression in US children's ability to handle increases in relational complexity and distraction from object similarity during analogical reasoning. In contrast, changes in how relations are represented in the model best capture cross-cultural differences in performance between children of the same ages (3-4 years) in the United States and Hong Kong. We use these results and simulations to argue that the development of analogical reasoning in children may best be conceptualized as an equilibrium between knowledge accretion and the maturation of information processing capability.     

Relational integration in older adults

Reasoning requires making inferences based on information gleaned from a set of relations. The relational complexity of a problem increases with the number of relations that must be considered simultaneously to make a correct inference. Previous work (Viskontas, Morrison, Holyoak, Hummel, & Knowlton, ) has shown that older adults have difficulty integrating multiple relations during analogical reasoning, especially when required to inhibit irrelevant information. We report two experiments that examined the ability to integrate multiple relations in younger, middle-aged, and older adults performing two other reasoning tasks. These tasks systematically varied relational complexity, and required either inductive reasoning (a version of the Raven's Matrices Task) or transitive inference. Our results show that as people age they have increasing difficulty in solving problems that require them to integrate multiple relations. This difficulty may stem from a decrease in working memory capacity.     

Constraints on Analogical Inference

The ability to reason by analogy is particularly important because it permits the extension of knowledge of a target domain by virtue of its similarity to a base domain via a process of analogical inference. The general procedure for analogical inference involves copying structure from the base to the target in which missing information is generated, and substitutions are made for items for which analogical correspondences have already been found. A pure copying with substitution and generation process is too profligate to be useful, and so constraints must be placed on what information is to be carried over. In this paper, the importance of systematicity as a constraint on inference is explored in four studies in which subjects find correspondences between domains and also make inferences. This work suggests that people prefer to make inferences of information connected to systematic correspondences between domains. A second important theme of this paper is that violations of one-to-one mapping can lead to inconsistent object substitutions in inference. The data reveal no such inconsistent substitutions in people's inferences, suggesting that they do respect one-to-one mapping in analogical inference. These findings are discussed relative to four prominent computational models of analogical mapping and inference.     

儿童类比推理的影响因素及干预促进

类比推理这一重要认知能力能够帮助儿童在未经历过的复杂情况下进行推断和学习。近年来研究者主要从行为研究、计算机模型和眼动技术的角度探究了儿童抑制控制和工作记忆在类比推理中的交互作用模式及类比推理策略对类比推理的影响。在此基础上,研究者围绕语言标签和物理表征两方面对儿童类比推理进行了干预研究。儿童类比推理的未来研究应着眼于改进研究方法、关注类比推理各加工阶段影响因素及加强儿童类比推理策略的干预应用研究。