Behavior systems and reinforcement: an integrative approach.

Most traditional conceptions of reinforcement are based on a simple causal model in which responding is strengthened by the presentation of a reinforcer. I argue that reinforcement is better viewed as the outcome of constraint of a functioning causal system comprised of multiple interrelated causal sequences, complex linkages between causes and effects, and a set of initial conditions. Using a simplified system conception of the reinforcement situation, I review the similarities and drawbacks of traditional reinforcement models and analyze the recent contributions of cognitive, regulatory, and ecological approaches. Finally, I show how the concept of behavior systems can begin to incorporate both traditional and recent conceptions of reinforcement in an integrative approach.     

Why Combine Logics?

Combining logics has become a rapidly expanding entreprise that is inspired mainly by concerns about modularity and the wish to join together tailor made logical tools into more powerful but still manageable ones. A natural question is whether it offers anything new over and above existing standard languages.By analysing a number of applications where combined logics arise, we argue that combined logics are a potentially valuable tool in applied logic, and that endorsements of standard languages often miss the point. Using the history of quantified modal logic as our main example, we also show that the use of combined structures and logics is a recurring theme in the analysis of existing logical systems.     

中学生特质焦虑与其影响因素的模型建构

该研究旨在建构特质焦虑与其影响因素的关系模型。文中提出了影响特质焦虑的三个潜变量 ,分别是人格、学业压力、环境。其中人格包括自卑倾向和内向性格两个指示变量 ,学校压力包括学业压力和人际困扰两个指示变量 ,环境包括不良社会影响、学校适应不良、身体虚弱和父母不良教养方式等指示变量。研究结果发现 ,人格和学校压力直接导致特质焦虑 ,环境通过对人格和学校压力产生影响而间接影响特质焦虑 ,同时 ,人格对学校压力产生影响     

因果判断中经验与共变信息的结合及各自作用

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,从而将经验和共变信息在因果判断中所起到的作用分离了出来。结果表明：（1）个体综合两种信息进行因果判断的过程既不是简单的相加操作,也不是使用经验信息控制共变信息的进入,而是先判断经验信息,再判断共变信息是否与之一致,当出现不一致的情况时又重新考虑经验信息。（2）在改变先前判断的过程中,经验信息所起的作用更大,其中又以当其证明待判断原因不可信时所产生的改变更大。     

Some probabilistic models of best, worst, and best-worst choices

Over the past decade or so, a choice design in which a person is asked to select both the best and the worst option in an available set of options has been gaining favor over more traditional designs, such as where the person is asked, for instance, to: select the best option; select the worst option; rank the options; or rate the options. In this paper, we develop theoretical results for three overlapping classes of probabilistic models for best, worst, and best-worst choices, with the models in each class proposing specific ways in which such choices might be related. The models in these three classes are called random ranking and random utility, joint and sequential, and ratio scale. We include some models that belong to more than one class, with the best known being the maximum-difference (maxdiff) model, summarize estimation issues related to the models, and formulate a number of open theoretical problems.     

Statistical models of syntax learning and use

This paper shows how to define probability distributions over linguistically realistic syntactic structures in a way that permits us to define language learning and language comprehension as statistical problems. We demonstrate our approach using lexical‐functional grammar (LFG), but our approach generalizes to virtually any linguistic theory. Our probabilistic models are maximum entropy models. In this paper we concentrate on statistical inference procedures for learning the parameters that define these probability distributions. We point out some of the practical problems that make straightforward ways of estimating these distributions infeasible, and develop a “pseudo‐likelihood” estimation procedure that overcomes some of these problems. This method raises interesting questions concerning the nature of the data available to a language learner and the modularity of language learning and processing.     

Believing in Miracles

Classical Christian definitions of miracle speak of events transcending the natural powers of objects. A personal creator, I argue, might well cause such events in order to achieve a supernatural purpose—bringing creatures to eternal life. Miracles—events transcending natural powers, disclosing and realizing the divine purpose—would then be integral to the rational order of nature. David Hume' arguments against believing reports of miracles are shown to be very weak. Laws of nature, I suggest, are best seen not as exceptionless rules but as context–dependent realizations of natural powers. In that context miracles transcend the natural order not as "violations" but as intelligible realizations of a divine supernatural purpose. Miracles are not parts of scientific theory but can be parts of a web of rational belief fully consistent with science.     

When Is Genetic Reasoning Not Fallacious?

Attempts to evaluate a belief or argument on the basis of its cause or origin are usually condemned as committing the genetic fallacy. However, I sketch a number of cases in which causal or historical factors are logically relevant to evaluating a belief, including an interesting abductive form that reasons from the best explanation for the existence of a belief to its likely truth. Such arguments are also susceptible to refutation by genetic reasoning that may come very close to the standard examples given of supposedly fallacious genetic reasoning.     

客体连续性的加工机制

把先前和现在遇到的客体视为同一个体的现象就可以称为客体连续性。目前对客体连续性的形成主要存在四种解释机制：相似理论、时空理论、种类理论和因果理论。研究者对时空理论中时空信息和客体表面特征信息, 种类理论和因果理论在此过程中所起的作用存在争论。今后应构建相似、种类、因果理论的实验范式, 改进时空、种类和因果理论实验设计的不足并把客体连续性的研究从视觉领域拓展到到嗅觉、听觉等领域。