联结主义神经网络及其在心理学中的应用

现代联结主义是神经科学、信息科学和心理科学融合生成的产物,神经网络是依据联结土义理论设计的模拟人脑神经系统的模型。该章首先介绍了神经网络及其特性,在对生物神经元和人工神经元的结构和功能进行比较的基础上,重点介绍了神经网络模型的结构、分类、激活规则以及学习规则。最后简要讨论了联结主义神经网络模型在心理学中的一些应用及存在的问题。     

认知主义与联结主义之比较

认知主义的研究定向和联结主义的研究定向是广义的现代认知心理学的两种主要研究范式。这两种研究范式都各有自己的研究内容和方法论,也取得了各自不同的成就,同时也存在各自不同的问题。通过对两种研究范式的比较,我们可以清楚地认识到二者的相互沟通和融合才是认知心理学未来发展的必然趋势。     

现代认知心理学关于图式模型的研究

对现代认知心理学关于知识图式的研究作了系统的阐述,分析了产生式系统取向和联结主义取向的优缺点。指出：图式模型研究的整合观是近来及以后认知心理学研究的主要课题之一。     

联结主义：认知过程的新解释和认知科学的新发展

联结主义：认知过程的新解释和认知科学的新发展葛鲁嘉（吉林大学）本世纪６０年代兴起的认知革命，在７０年代取决了决定性的胜利。认知心理学替代行为主义心理学成了科学心理学的主流，并很快席卷了心理学的大多数分支。认知科学则汇集了认知心理学、人工智能、语言学、...     

西方理论心理学研究的新特点

理论心理学研究的复兴是近年来西方心理学发展的新特点。西方理论心理学研究的重点,并不是通过理论化的简单转向来克服心理学发展中的困难,或以总体的、一般的抽象术语重新发明元理论,而是力图在提高理论研究方式的科学化水平基础上,加强对具体的、中等水平的亚理论问题的整合性学术探讨。进一步寻求心理学理论研究走向繁荣的学科内在发展机制。     

库恩的后达尔文式康德主义中的心理学方法论探析

库恩的后达尔文式康德主义主要是一种方法论,对当今的心理学发展具有重要意义。它为文化人类学方法在心理学中的运用与发展奠定了理论基础,为重新审视心理学知识和学科发展提供了一个新视角,促进了多元文化等心理学取向形成与发展和解释学方法的扶正,加强了普遍联系观和整体化或系统化方法在心理学中的地位,有助于心理学哲学研究的兴起,为理论心理学的复兴打开了方便之门。     

语义记忆的联结主义模型述评

联结主义研究取向是近十几年来认知心理学中一种主导性的指导思想、记忆研究领域已出现了不少联结主义模型。本文主要介绍有关语义记忆的联结主义模型的历史演变,并阐述该模型特点及基本结构假设、加工假设和控制假设,最后对该模型的优点和局限进行评价。     

试论西方马克思主义心理学取向的特点及成就

当今西方心理学研究中盛行着形形色色的马克思主义流派, 除了传统的精神分析马克思主义、人本心理学马克思主义和辩证法心理学等思潮之外, 还涌现出了实证主义心理学的马克思主义、女权主义心理学的马克思主义、批判心理学的马克思主义和多元主义辩证法等新取向, 其中批判心理学已成为发展的主流。马克思主义是我们的立国之本, 随着世界范围内马克思主义研究运动的日益高涨, 如何认识西方马克思主义的心理学理论资源, 是我们中国心理学研究需要进一步探讨的一个重要理论和现实问题。     

试论康德心理学思想及其对当代的影响

康德著作中蕴含着丰富的心理学思想,其在继承沃尔夫理性心理学与经验心理学二分的基础上,通过批评理性心理学,消解了我思的主体地位,为解决二元论问题做出了重要努力;通过批评经验心理学,指明了心理学在成长为一门科学过程中必须面对的诸多问题。新康德主义在继承并改造康德思想的过程中,发展出一系列影响深远的心理学理论;认知心理学的重要代表人物皮亚杰基于对康德思想独具特色的把握,提出了发生认识论;而当代认知科学的图式理论,则完全是建基于对康德经验图式理论框架的全面继承上。     

试论理论心理学及其应用价值

理论心理学是近20年来涌现出的新学科。这是一门以理论思维方法对心理学的基本问题和规律进行探索的科学,已逐渐汇成为心理学各分支学科的理论基础。理论心理学在心理学中的地位,就应像理论物理学、理论化学在物理学和化学中一样,是心理学的学科体系中一个极为重要和不可缺少的组成部分。理论心理学并不是抽象的哲学建构,它也十分关注实践应用问题。当前理论心理学在西方已出现了两种比较成熟的行动应用模式。     

The curious case of the Chinese gym

Searle has recently used two adaptations of his Chinese room argument in an attack on connectionism. I show that these new forms of the argument are fallacious. First I give an exposition of and rebuttal to the original Chinese room argument, and then a brief introduction to the essentials of connectionism.     

Connectionism and the Philosophical Foundations of Cognitive Science

This is an overview of recent philosophical discussion about connectionism and the foundations of cognitive science. Connectionist modeling in cognitive science is described. Three broad conceptions of the mind are characterized, and their comparative strengths and weaknesses are discussed: (1) the classical computation conception in cognitive science; (2) a popular foundational interpretation of connectionism that John Tienson and I call "non-sentential computationalism"; and (3) an alternative interpretation of connectionism we call "dynamical cognition." Also discussed are two recent philosophical attempts to enlist connectionism in defense of eliminativism about folk psychology.     

Implicit and explicit memory: Implications for the symbol-manipulation versus connectionism controversy

Summary This paper deals with three issues. First, the symbol-manipulation versus connectionism controversy is discussed briefly. Both can be seen as formalisms or languages for describing human behavior, but it is argued that these languages are not fully equivalent. The importance of the ability of connectionist models to learn autonomously, often underestimated, allows them to perform tasks that may defy formalization. Secondly, the structural and functional characteristics of a new connectionist learning model are presented. It avoids some of the psychological and biological implausibilities of currently popular models and solves some of the problems and shortcomings of these models. Thirdly, some simulation results are presented. The model successfully simulates the dissociation between explicit and implicit memory performance as found in patients with anterograde amnesia. This simulation provides an example of the advantages of using the connectionist language in the domain of memory psychology. It is also a good example of how psychological evidence can be used to improve connectionist models.The second author is supported by the Dutch Organization for Scientific Research (NWO)     

Type a behaviour pattern as a risk factor after myocardial infarction: A review

Abstract

This paper is a response to Eiser's (1996) call for a unifying theoretical perspective that would bridge the gap between 'individualistic and ‘social’ approaches to studying human social behaviour in general, and health behaviour in particular. While agreeing with Eiser's premise that it makes no sense to study cognition, affect, and behaviour independently of social context, the present paper takes issue with certain features of his argument that a connectionist approach provides the needed unifying theoretical framework. It is suggested that if connectionism can describe the psychological processes underlying social behavior better than non-connectionist theories, this would provide more compelling evidence of its value than claims that it affords new theoretical insights.     

Connectionism: Is it a paradigm shift for psychology?

Connectionism is a method of modeling cognition as the interaction of neuron-like units. Connectionism has received a gread deal of interest and may represent a paradigm shift for psychology. The nature of a paradigm shift (Kuhn, 1970) is reviewed with respect to connectionism. The reader is provided an overview on connectionism including: an introduction to connectionist modeling, new issues it emphasizes, a brief history, its developing sociopolitical impact, theoretical impact, and empirical impact. Cautions, concerns, and enthusiasm for connectionism are expressed.     

Extended network learning error: A new way of conceptualising chronic fatigue syndrome

Abstract

The cause of chronic fatigue syndrome (CFS) is controversial: psychological, hypothalamic and immune mechanisms have been proposed as well as the possibility of some form of interaction between these mechanisms. Patients' own conceptual models vary and sometimes adversely affect self-management. This paper suggests an interactional way of conceptualising CFS using developments in complexity theory (networks, parallel processing or connectionism). I propose that the neurological, immune and endocrine systems are pan of a single, self-regulatory, extended brain-body network. Furthermore, that CFS is caused by self-organisational change in this extended network created by normally adaptive error-sensitive learning rules that malfunction when physiological and psychological challenges coincide. This psychoneuroimniunoendocrinological model shows how previously proposed mechanisms could interact to cause CFS. explains the heterogeneity of the presentation of the disease, and provides a conceptual model that may be acceptable to patients but is also consistent with effective self-management.     

Connectionism and Self: James,Mead, and the Stream of Enculturated Consciousness

William James conceptualized I, the self as subject as a stream of consciousness. When this conception is augmented with George Herbert Mead's view of self as a radically socialized and enculturated process, a result is the James-Mead model of dynamic self as a stream of enculturated consciousness. In this paper, we argue that connectionism is best suited to theorize this challenging notion. Based on the view that a connectionist model should describe psychological processes that carry out psychological functions grounded in a biological living system, we propose the I-SELF (Imitative and Sequence Learning Functional) model, which is designed to capture the temporal dynamics of a stream of consciousness whose content can be acquired via symbolically mediated social interaction with others in society. We identify four implications of the James-Mead model of dynamic self (embodiment, narrative and self, individual and collective self, and culture and self), and report computer simulations to show the utility of I-SELF in conceptualizing the dynamic self-processes in the contemporary social psychological literature. Theoretical and metatheoretical implications of the connectionist approach to self are discussed.     

基于联结主义的连续记分IRT模型的项目参数和被试能力估计

运用联结主义中的级连相关模型对于小样本条件下的连续记分项目反应理论 (IRT)模型的项目参数和被试能力进行了估计。一组被试对于一组项目的反应矩阵作为级连相关模型的输入 ,这组被试的能力θ或该组项目的参数a、b和c作为该模型的输出 ,对神经网络进行训练使之具备了估计θ,a ,b或c的能力。计算机模拟的实验表明 ,如果测验中有少量项目取自于题库 ,就可以运用联结主义方法对IRT参数和被试能力进行较好的估计     

Empiricism without magic: transformational abstraction in deep convolutional neural networks

In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often appealing to a faculty of abstraction. Rationalists have frequently complained, however, that empiricists never adequately explained how this faculty of abstraction actually works. In this paper, I tie these two questions together, to the mutual benefit of both disciplines. I argue that the architectural features that distinguish DCNNs from earlier neural networks allow them to implement a form of hierarchical processing that I call “transformational abstraction”. Transformational abstraction iteratively converts sensory-based representations of category exemplars into new formats that are increasingly tolerant to “nuisance variation” in input. Reflecting upon the way that DCNNs leverage a combination of linear and non-linear processing to efficiently accomplish this feat allows us to understand how the brain is capable of bi-directional travel between exemplars and abstractions, addressing longstanding problems in empiricist philosophy of mind. I end by considering the prospects for future research on DCNNs, arguing that rather than simply implementing 80s connectionism with more brute-force computation, transformational abstraction counts as a qualitatively distinct form of processing ripe with philosophical and psychological significance, because it is significantly better suited to depict the generic mechanism responsible for this important kind of psychological processing in the brain.     

Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning

In this paper, it is argued that single function dual process theory is a more credible psychological account of non-monotonicity in human conditional reasoning than recent attempts to apply logic programming (LP) approaches in artificial intelligence to these data. LP is introduced and among other critiques, it is argued that it is psychologically unrealistic in a similar way to hash coding in the classicism vs. connectionism debate. Second, it is argued that causal Bayes nets provide a framework for modelling probabilistic conditional inference in System 2 that can deal with patterns of inference LP cannot. Third, we offer some speculations on how the cognitive system may avoid problems for System 1 identified by Fodor in 1983. We conclude that while many problems remain, the probabilistic single function dual processing theory is to be preferred over LP as an account of the non-monotonicity of human reasoning.