其它可能原因对于因果共变信息作用的影响

研究使用相继呈现信息的方法控制了被试获得信息的顺序,将其它可能原因在因果判断过程中所起到的作用分离了出来,并按照其对不同共变信息的影响进行了分析。研究结果表明：(1)其它可能原因会影响到被试利用因果共变信息而进行的因果推断。(2)其它可能原因与待判断原因共同存在的程度在很大程度上影响着其它可能原因所起到的作用。(3)其它可能原因对于不同共变信息的影响有着明显的差别。     

项目诊断性在特征推理中作用的研究

该研究在Murphy等人2005年研究的基础上,探讨了项目诊断性对特征推理的影响。实验1探讨归类情况下,项目诊断性对特征推理的影响。实验2探讨不归类情况下,项目诊断性对特征推理的影响。实验结果表明,归类与否决定项目诊断性是否影响特征推理。在归类情况下,高低两种诊断性条件下的特征概率判断没有差异,表明归类情况下,项目诊断性不影响特征推理;在不归类的情况下,高低两种诊断性条件下的特征概率判断存在显著差异,表明不归类情况下,项目诊断性影响特征推理。     

The Future is Bright? Effects of Mood on Perception of the Future

Most people believe that the future will bring them more good things than bad, and therefore have high hopes for the future (MacLeod et al. Cogn Emot 10:69–85, 1996). However, many patients with mood disorders do not hold this positive belief about the future. At the extreme, low expectations of positive outcomes in the future can lead to feelings of hopelessness (O’Connor et al. Psychol Health Med 5:155–161, 2000). This paper aims to extend the literature on subjective probability of future events, using a mood induction paradigm to examine the effects of transient mood change on perceived likelihood of future events in a non-clinical community sample. Participants rated likelihood of future events from a standardized list and from their own lives. Ratings were made in both normal and experimentally-induced positive or negative mood. Results show that self-generated future events were perceived to be more likely than those from a standardized list, and that negative mood significantly biased perceived likelihood of other-generated future events. Participants rating standardized list events saw positive outcomes as less likely and negative outcomes as more likely in induced negative mood than they did in normal mood. Mood had no effect on ratings of self-generated events. Possible directions for future research are discussed.

A new definition of well-behaved discrimination functions

A discrimination function shows the probability or degree with which stimuli are discriminated from each other when presented in pairs. In a previous publication [Kujala, J.V., & Dzhafarov, E.N. (2008). On minima of discrimination functions. Journal of Mathematical Psychology, 52, 116–127] we introduced a condition under which the conformity of a discrimination function with the law of Regular Minimality (which says, essentially, that “being least discriminable from” is a symmetric relation) implies the constancy of the function’s minima (i.e., the same level of discriminability of every stimulus from the stimulus least discriminable from it). This condition, referred to as “well-behavedness,” turns out to be unnecessarily restrictive. In this note we give a significantly more general definition of well-behavedness, applicable to all Hausdorff arc-connected stimulus spaces. The definition employs the notion of the smallest transitively and topologically closed extension of a relation. We provide a transfinite-recursive construction for this notion and illustrate it by examples.     

Causal-based property generalization

A central question in cognitive research concerns how new properties are generalized to categories. This article introduces a model of how generalizations involve a process of causal inference in which people estimate the likely presence of the new property in individual category exemplars and then the prevalence of the property among all category members. Evidence in favor of this causal-based generalization (CBG) view included effects of an existing feature's base rate (Experiment 1), the direction of the causal relations (Experiments 2 and 4), the number of those relations (Experiment 3), and the distribution of features among category members (Experiments 4 and 5). The results provided no support for an alternative view that generalizations are promoted by the centrality of the to-be-generalized feature. However, there was evidence that a minority of participants based their judgments on simpler associative reasoning processes.     

A Note on Goodman's Theorem

Goodman's theorem states that intuitionistic arithmetic in all finite types plus full choice, HA + AC, is conservative over first-order intuitionistic arithmetic HA. We show that this result does not extend to various subsystems of HA, HA with restricted induction.     

Projectibility and Explainability or How to Draw a New Picture of Inductive Practices

Summary  Goodman published his “riddle” in the middle of the 20th century and many philosophers have attempted to solve it. These attempts almost all shared an assumption that, I shall argue, might be wrong, namely, the assumption that when we project from cases we have examined to cases we have not, what we project are predicates (and that this projectibility is an absolute property of some predicates). I shall argue that this assumption, shared by almost all attempts at a solution, looks wrong, because, in the first place, what we project are generalizations and not predicates, and a generalization is projectible (or unprojectible) relative to a given context. In this paper I develop the idea of explainable–projectible generalizations versus unexplainable–unprojectible generalizations, relative to a specific context. My main claim is that we rationally project a generalization if and only if we rationally believe that there is something that explains the general phenomenon that the generalized statement in question asserts to obtain, and that a generalization is projectible, if and only if its putative truth can be explained, whether we know that it can be or not.     

Induction of Relational Schemas: Common Processes in Reasoning and Complex Learning

Five experiments were performed to test whether participants induced a coherent representation of the structure of a task, called a relational schema, from specific instances. Properties of a relational schema include: An explicit symbol for a relation, a binding that preserves the truth of a relation, potential for higher-order relations, omnidirectional access, potential for transfer between isomorphs, and ability to predict unseen items in isomorphic problems. However relational schemas are not necessarily coded in abstract form. Predictions from relational schema theory were contrasted with predictions from configural learning and other nonstructural theories in five experiments in which participants were taught a structure comprised of a set of initial-state,operator → end-state instances. The initial-state,operator pairs were presented and participants had to predict the correct end-state. Induction of a relational schema was achieved efficiently by adult participants as indicated by ability to predict items of a new isomorphic problem. The relational schemas induced showed the omnidirectional access property, there was efficient transfer to isomorphs, and structural coherence had a powerful effect on learning. The “learning to learn” effect traditionally associated with the learning set literature was observed, and the long-standing enigma of learning set acquisition is explained by a model composed of relational schema induction and structure mapping. Performance was better after reversal of operators than after shift to an alternate structure, even though the latter entailed more overlap with previously learned tasks in terms of the number of configural associations that were preserved. An explanation for the reversal shift phenomenon in terms of induction and mapping of a relational schema is proposed. The five experiments provided evidence supporting predictions from relational schema theory, and no evidence was found for configural or nonstructural learning theories.     

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