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Journal articles on the topic 'Connectionsim; Cognitive science'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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1

Milojevic, Miljana, and Vanja Subotic. "The exploratory status of postconnectionist models." Theoria, Beograd 63, no. 2 (2020): 135–64. http://dx.doi.org/10.2298/theo2002135m.

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This paper aims to offer a new view of the role of connectionist models in the study of human cognition through the conceptualization of the history of connectionism - from the simplest perceptrons to convolutional neural nets based on deep learning techniques, as well as through the interpretation of criticism coming from symbolic cognitive science. Namely, the connectionist approach in cognitive science was the target of sharp criticism from the symbolists, which on several occasions caused its marginalization and almost complete abandonment of its assumptions in the study of cognition. Crit

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2

Gasser, Michael. "Connectionism and Universals of Second Language Acquisition." Studies in Second Language Acquisition 12, no. 2 (1990): 179–99. http://dx.doi.org/10.1017/s0272263100009074.

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This article examines the implications of connectionist models of cognition for second language theory. Connectionism offers a challenge to the symbolic models which dominate cognitive science. In connectionist models all knowledge is embodied in a network of simple processing units joined by connections which are strengthened or weakened in response to regularities in input patterns. These models avoid the brittleness of symbolic approaches, and they exhibit rule-like behavior without explicit rules. A connectionist framework is proposed within which hypotheses about second language acquisiti

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Bainbridge, William Sims. "Social cognition of religion." Behavioral and Brain Sciences 29, no. 5 (2006): 463–64. http://dx.doi.org/10.1017/s0140525x06239104.

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Research on religion can advance understanding of social cognition by building connections to sociology, a field in which much cognitively oriented work has been done. Among the schools of sociological thought that address religious cognition are: structural functionalism, symbolic interactionism, conflict theory, phenomenology, and, most recently, exchange theory. The gulf between sociology and cognitive science is an unfortunate historical accident.

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Seidenberg, Mark S. "Connectionist Models and Cognitive Theory." Psychological Science 4, no. 4 (1993): 228–35. http://dx.doi.org/10.1111/j.1467-9280.1993.tb00266.x.

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Connectionist models have come to play an important role in cognitive science and in cognitive neuroscience, yet their role in explaining behavior is not necessarily obvious and has generated considerable debate. Connectionism is a body of tools and ideas that can be used in different ways. It can be treated as a form of simulation modeling in which the goal is to implement preexisting theories. In this approach, connectionist models function as a kind of statistical tool, a way of analyzing a complex set of data. Connectionism can also be seen as providing a small set of general theoretical p

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Bret, Michel, Marie-Hélène Tramus, and Alain Berthoz. "Interacting with an Intelligent Dancing Figure: Artistic Experiments at the Crossroads between Art and Cognitive Science." Leonardo 38, no. 1 (2005): 46–53. http://dx.doi.org/10.1162/leon.2005.38.1.46.

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The authors (a neurophysiologist and two computer artists) give an account of a collaboration that took place within the framework of a study—cum— artistic experiment on virtual interactive figures at the boundary of art and cognitive science. This study, called “‘Intelligent’ Interactivity (Connectionism, Evolutionary Science and Artificial Life) in Digital Arts in Relation with the Physiology of the Perception of Action and Movement,” was supported by the Cognitique 2000 Program on Art and Cognition, an initiative of the French Ministry of Research.

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6

Harder, Peter, and Ole Togeby. "Pragmatics, cognitive science and connectionism." Journal of Pragmatics 20, no. 5 (1993): 467–92. http://dx.doi.org/10.1016/0378-2166(93)90040-v.

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7

Zumalabe Makirriain, José María. "Acerca del carácter representacional de la mente. La mente representacional." Psychology, Society, & Education 6, no. 2 (2017): 125. http://dx.doi.org/10.25115/psye.v6i2.513.

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Resumen: Desde las ciencias cognitivas se entiende el pensamiento en términos de estructuras de representaciones mentales sobre las que operan procesos computacionales. En el modelo representacional-computacional de la mente se recurre a una compleja analogía triádica que vincula mente, cerebro y ordenadores. La mayoría de estos modelos son simbólicos, aunque también existen modelos representacionales no simbólicos (conexionismo) y modelos cognitivos no representacionales de la mente. El análisis de los diferentes enfoques cognitivos sobre las representaciones y los procesos mentales en el mar

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8

Sterelny, Kim. "Connectionism Rules, OK?" Dialogue 32, no. 3 (1993): 545–54. http://dx.doi.org/10.1017/s0012217300012312.

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Those familiar with Paul Churchland's earlier work will expect A Neuro-computational Perspective to be lively, provocative and interesting. They will not be disappointed. Churchland is best known for his sceptical view of belief-desire psychology. He suspects this theory is hopelessly false. This welcome collection of his essays includes this work but also his papers on the subjective aspects of the mind and his more recent adventures in philosophy of science. Three themes unify the collection: an anti-sententialist view of cognition, an emphasis on the plasticity of the human mind and a stron

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9

Stephan, Achim. "Was zeichnet eine moderne Auffassung von Geist aus?" History of Philosophy and Logical Analysis 18, no. 1 (2015): 114–28. http://dx.doi.org/10.30965/26664275-01801009.

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‘Having a mind’ is construed as having a variety of mental capacities such as perceiving, memorizing, learning, or reasoning. In cognitive science, these capacities are studied from an integrative trans-disciplinary perspective that combines anthropology, artificial intelligence, computational linguistics, neuroscience, philosophy and psychology. To approach mental phenomena by combining philosophical insights with those from the natural sciences is part of the Aristotelian tradition. Accordingly, the paper also portrays the most salient models of mental processing – the computer model, connec

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10

Subotic, Vanja. "Folk psychology, eliminativism, and the present state of connectionism." Theoria, Beograd 64, no. 1 (2021): 173–96. http://dx.doi.org/10.2298/theo2101173s.

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Three decades ago, William Ramsey, Steven Stich & Joseph Garon put forward an argument in favor of the following conditional: if connectionist models that implement parallelly distributed processing represent faithfully human cognitive processing, eliminativism about propositional attitudes is true. The corollary of their argument (if it proves to be sound) is that there is no place for folk psychology in contemporary cognitive science. This understanding of connectionism as a hypothesis about cognitive architecture compatible with eliminativism is also endorsed by Paul Churchland, a radic

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11

Oaksford, Mike, Nick Chater, and Keith Stenning. "Connectionism, classical cognitive science and experimental psychology." AI & Society 4, no. 1 (1990): 73–90. http://dx.doi.org/10.1007/bf01889765.

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12

Green, Christopher D. "Scientific Models, Connectionist Networks, and Cognitive Science." Theory & Psychology 11, no. 1 (2001): 97–117. http://dx.doi.org/10.1177/0959354301111008.

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13

Grossberg, Stephen. "Bring ART into the ACT." Behavioral and Brain Sciences 26, no. 5 (2003): 610–11. http://dx.doi.org/10.1017/s0140525x03290130.

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ACT is compared with a particular type of connectionist model that cannot handle symbols and use nonbiological operations which do not learn in real time. This focus continues an unfortunate trend of straw man debates in cognitive science. Adaptive Resonance Theory, or ART-neural models of cognition can handle both symbols and subsymbolic representations, and meet the Newell criteria at least as well as connectionist models.

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14

French, Robert M., and Elizabeth Thomas. "The dynamical hypothesis: One battle behind." Behavioral and Brain Sciences 21, no. 5 (1998): 640–41. http://dx.doi.org/10.1017/s0140525x98361737.

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What new implications does the dynamical hypothesis have for cognitive science? The short answer is: none. The target article is basically an attack on traditional symbolic artificial intelligence (AI) and differs very little from prior connectionist criticisms of it. For the past 10 years, the connectionist community has been well aware of the necessity of using (and understanding) dynamically evolving, recurrent network models of cognition.

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15

Lloyd, Dan. "Connectionism in the golden age of cognitive science." Behavioral and Brain Sciences 11, no. 1 (1988): 42–43. http://dx.doi.org/10.1017/s0140525x00052626.

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16

Reilly, Ronan. "On the Relationship Between Connectionism and Cognitive Science." Irish Journal of Psychology 10, no. 2 (1989): 162–87. http://dx.doi.org/10.1080/03033910.1989.10557740.

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17

Horgan, Terence. "Connectionism and the Philosophical Foundations of Cognitive Science." Metaphilosophy 28, no. 1-2 (1997): 1–30. http://dx.doi.org/10.1111/1467-9973.00039.

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Gibbs Jr, Raymond W., and Ana Cristina Pelosi Silva de Macedo. "Metaphor and embodied cognition." DELTA: Documentação de Estudos em Lingüística Teórica e Aplicada 26, spe (2010): 679–700. http://dx.doi.org/10.1590/s0102-44502010000300014.

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The present paper briefly describes recent advances in cognitive science on the embodied nature of human cognition with the aim to better situating contemporary work on embodied metaphor in language and thought. We do this by talking about key experimental findings in five areas main areas of research in cognitive science: perception, concepts, mental imagery, memory, and language processing (Gibbs 2006a) We also describe some psycholinguistic studies on embodied metaphor understanding, and offer some details on one series of experiments in regard to people's embodied understanding of the DIFF

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19

Smolensky, Paul. "On the proper treatment of connectionism." Behavioral and Brain Sciences 11, no. 1 (1988): 1–23. http://dx.doi.org/10.1017/s0140525x00052432.

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AbstractA set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models and neural mod

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Movellan, Javier R., and Jonathan D. Nelson. "Probabilistic functionalism: A unifying paradigm for the cognitive sciences." Behavioral and Brain Sciences 24, no. 4 (2001): 690–92. http://dx.doi.org/10.1017/s0140525x0154008x.

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The probabilistic analysis of functional questions is maturing into a rigorous and coherent research paradigm that may unify the cognitive sciences, from the study of single neurons in the brain to the study of high level cognitive processes and distributed cognition. Endless debates about undecidable structural issues (modularity vs. interactivity, serial vs. parallel processing, iconic vs. propositional representations, symbolic vs. connectionist models) may be put aside in favor of a rigorous understanding of the problems solved by organisms in their natural environments. [Shepard; Tenenbau

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21

Horgan, Terence, and John Tienson. "Levels of Description in Nonclassical Cognitive Science." Royal Institute of Philosophy Supplement 34 (March 1993): 159–88. http://dx.doi.org/10.1017/s1358246100002496.

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David Marr (1982) provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science (classicism, as we will call it henceforth). Thus, by focusing on levels of description, one can sharpen foundational differences b

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22

Berent, Iris. "The Algebraic Mind: Integrating Connectionism and Cognitive Science (review)." Language 78, no. 3 (2002): 569–71. http://dx.doi.org/10.1353/lan.2002.0146.

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23

Ellis, Nick. "COGNITIVE APPROACHES TO SLA." Annual Review of Applied Linguistics 19 (January 1999): 22–42. http://dx.doi.org/10.1017/s0267190599190020.

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Getting to know a second language is an act of cognition par excellence. Yet 'Cognitive Approaches to SLA' implies something more than the general research enterprise of SLA. It highlights the goals of cognitive psychologists who search for explanations of second language cognition in terms of mental representations and information processing. It places SLA within the broader remit of cognitive scientists, who—influenced by Marr (1982) to seek understanding at all three levels of function, algorithm, and hardware—work in collaborations involving cognitive psychology, linguistics, epistemology,

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24

Robinson, Douglas. "Reframing translational norm theory through 4EA cognition." Translation, Cognition & Behavior 3, no. 1 (2020): 122–42. http://dx.doi.org/10.1075/tcb.00037.rob.

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Abstract Norm theory was invented in 1986, by Daniel Kahneman and Dale T. Miller, as a decision-science subdiscipline of psychology, but with close connections with emerging embodied, embedded, enactive, extended and affective (4EA) cognitive science. Notably, they gave affective response a key role in marking not only the intensity but the cognitive load of norm-formative decision-making. A few years later, in the early 1990s, Gideon Toury, Andrew Chesterman, and other translation scholars began to theorize translational norms—with a very different model that apparently owed nothing to Kahnem

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Hanson, Stephen José, and David J. Burr. "What connectionist models learn: Learning and representation in connectionist networks." Behavioral and Brain Sciences 13, no. 3 (1990): 471–89. http://dx.doi.org/10.1017/s0140525x00079760.

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AbstractConnectionist models provide a promising alternative to the traditional computational approach that has for several decades dominated cognitive science and artificial intelligence, although the nature of connectionist models and their relation to symbol processing remains controversial. Connectionist models can be characterized by three general computational features: distinct layers of interconnected units, recursive rules for updating the strengths of the connections during learning, and “simple” homogeneous computing elements. Using just these three features one can construct surpri

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26

Fırıncı, Yusuf. "Ultramodern Psychology: A Vision Construction with Culture, Religion, Cognitive Science and Neurotheology." Spiritual Psychology and Counseling 4, no. 3 (2019): 275–308. http://dx.doi.org/10.37898/spc.2019.4.3.080.

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This research paper focuses on the evaluation of historical connections and interactions between psychology, psychiatry, psychologists, beliefs and religions. The argument of this research is; for developing future perspectives on psychology, religion can possibly provide historical and modern tools, as well as various other contributions. Within the scope of this research paper, the main idea and some other relevant arguments have been developed by evaluating historical facts and scientific analysis presented under the sub-sections of this essay, namely; psychology, beliefs and interdisciplin

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Sushchin, M. A. "Cognitive science: from paradigms to theoretical complexes." Philosophy of Science and Technology 26, no. 2 (2021): 5–22. http://dx.doi.org/10.21146/2413-9084-2021-26-1-5-22.

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This article deals with the task of understanding main theoretical movements in cognitive science, including classical computational cognitivism, connectionism, moderate embodied cognition, and predictive processing. For this purpose, the article analyzes the well-known post-positivist conceptions of philosophy of science developed by T. Kuhn, I. Lakatos, and L. Laudan, which focus not on individual theories, but on groups of theories. Despite the fact that all these well-known post-positivist conceptions describe well certain features of theoretical movements in cognitive science, none of the

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Gayler, Ross W., and Simon D. Levy. "Compositional connectionism in cognitive science II: the localist/distributed dimension." Connection Science 23, no. 2 (2011): 85–89. http://dx.doi.org/10.1080/09540091.2011.587505.

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29

McCloskey, Michael. "Networks and Theories: The Place of Connectionism in Cognitive Science." Psychological Science 2, no. 6 (1991): 387–95. http://dx.doi.org/10.1111/j.1467-9280.1991.tb00173.x.

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30

Li, Ping. "Bilingualism is in dire need of formal models." Bilingualism: Language and Cognition 5, no. 3 (2002): 213. http://dx.doi.org/10.1017/s1366728902253018.

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Each year the Cognitive Science Society honors David Rumelhart by awarding the Rumelhart Prize to an outstanding cognitive scientist whose research makes a significant contribution to the formal analysis of human cognition. Formal models of language, including those of Rumelhart and his associates, are well known to psycholinguists in the monolingual context. The formalism of language in the bilingual context, however, is lamentable: to this date, there are only a handful of models (connectionist or otherwise) that are designed specifically to account for bilingual language processing and acqu

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31

Sułkowski, Łukasz. "Management – from Epistemology by Methodology to Social Practice of Academia Cognitive Challenges in Management Science 2." Przedsiebiorczosc i Zarzadzanie 16, no. 2 (2015): 111–19. http://dx.doi.org/10.1515/eam-2015-0020.

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AbstractThe aim of the article is to present cognitive challenges in the area of management. Researchers and reflective managers still work on the identity of management belonging to the social sciences. The paper depicts the connections between cognitive problems (from the epistemological point of view), management methodology and social practice. Management sciences are parts of historical discourse and because of that epistemological and methodological levels have an impact on social practice. The main concern of this paper is the role of the management scientist, consultant and teacher. Th

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32

McMillen, Robert, and Tracy Henley. "Connectionism Isn’t Just for Cognitive Science: Neural Networks as Methodological Tools." Psychological Record 51, no. 1 (2001): 3–18. http://dx.doi.org/10.1007/bf03395383.

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33

Barnes, Dermot, and Peter John Hampson. "Stimulus Equivalence and Connectionism: Implications for Behavior Analysis and Cognitive Science." Psychological Record 43, no. 4 (1993): 617–38. http://dx.doi.org/10.1007/bf03395903.

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34

HOLYOAK, K. J. "A Connectionist View of Cognition: Parallel Distributed Processing." Science 236, no. 4804 (1987): 992–96. http://dx.doi.org/10.1126/science.236.4804.992.

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35

Dodig-Crnkovic, Gordana. "Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines." Philosophies 5, no. 3 (2020): 17. http://dx.doi.org/10.3390/philosophies5030017.

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The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is

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Dodig-Crnkovic, G. "Natural morphological computation as foundation of learning to learn in humans, other living organisms, and intelligent machines." Philosophical Problems of Information Technologies and Cyberspace, no. 1 (July 14, 2021): 4–34. http://dx.doi.org/10.17726/philit.2021.1.1.

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The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is

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37

Pinker, Steven. "On Language." Journal of Cognitive Neuroscience 6, no. 1 (1994): 92–98. http://dx.doi.org/10.1162/jocn.1994.6.1.92.

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Steven Pinker is a professor in the Department of Brain and Cognitive Sciences at MIT, and in 1994 will become director of its McDonnell-Pew Center for Cognitive Neuroscience. He received his B.K from McGill University in 1976 and his Ph.D. from Harvard University in 1979, both in experimental psychology, and taught at Harvard and Stanford before joining the faculty of MIT in 1982. He has done research in visual cognition and the psychology of language, and is the author of Language Learnability and Language Development (1984) and Learnability and Cognition (1989) and the editor of Visual Cogn

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38

Banan, Shahryar, Muhammad Ridwan, and Abdurahman Adisaputera. "A Study of Connectionism Theory." Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences 3, no. 3 (2020): 2335–42. http://dx.doi.org/10.33258/birci.v3i3.1181.

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The development of connectionism represents a paradigm shift in science. Connectionism has its root in cognitive and computational neuroscience. Likening the brain to a computer, connectionism tries to describe human mental abilities in terms of artificial neural networks. A neural network consists of a large number of nodes and units which are joined together to form an interconnection network. Within these interconnections, knowledge is distributed. Therefore learning is a processing by-product. This article is about the concept of connectionism, what it accounts for and what it doesn't take

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39

Poczobut, Robert, and Dariusz Surowik. "Introduction." Studies in Logic, Grammar and Rhetoric 48, no. 1 (2016): 7–9. http://dx.doi.org/10.1515/slgr-2016-0052.

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Abstract The problem of interfield integration in cognitive science has three closely connected aspects; they are to do with: a) the interdependencies between the levels of organization of cognitive systems (the substantive aspect), b) the intertheoretic connections between the subdisciplines of cognitive science (the methodological aspect), and c) the organization of research and interdisciplinary research projects conducted by scientists from different disciplines who employ a variety of research methods (the institutional aspect).

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40

Butler, Keith. "Representation and computation in a deflationary assessment of Connectionist cognitive science." Synthese 104, no. 1 (1995): 71–97. http://dx.doi.org/10.1007/bf01063676.

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41

Ezquerro, Jesús, and Fernando Martínez Manrique. "Intertheory Relations in Cognitive Science: Privileged Levels and Reductive Strategies." Crítica (México D. F. En línea) 36, no. 106 (2004): 55–103. http://dx.doi.org/10.22201/iifs.18704905e.2004.427.

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Research in cognitive science has often assumed the existence of a privileged level that unifies theoretical explanations arising from different disciplines. Philosophical accounts differ about the locus of those intertheory relations. In this paper, four different views are analyzed: classical, connectionist, pragmatist, and reductionist, as exemplified in the works of von Eckardt, Horgan and Tienson, Hardcastle, and Bickle, respectively. Their divergences are characterized in terms of the possibility of such a privileged level. The classical view favors a privileged computational level. The

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42

Boyer, Pascal. "Science, Erudition and Relevant Connections." Journal of Cognition and Culture 3, no. 4 (2003): 344–58. http://dx.doi.org/10.1163/156853703771818109.

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Karmiloff-Smith, Annette. "Précis ofBeyond modularity: A developmental perspective on cognitive science." Behavioral and Brain Sciences 17, no. 4 (1994): 693–707. http://dx.doi.org/10.1017/s0140525x00036621.

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AbstractBeyond modularityattempts a synthesis of Fodor's anticonstructivist nativism and Piaget's antinativist constructivism. Contra Fodor, I argue that: (1) the study of cognitive development is essential to cognitive science, (2) the module/central processing dichotomy is too rigid, and (3) the mind does not begin with prespecified modules; rather, development involves a gradual process of “modularization.” Contra Piaget, I argue that: (1) development rarely involves stagelike domain-general change and (2) domainspecific predispositions give development a small but significant kickstart by

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Park, H. J., and K. Friston. "Structural and Functional Brain Networks: From Connections to Cognition." Science 342, no. 6158 (2013): 1238411. http://dx.doi.org/10.1126/science.1238411.

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45

Metcalfe, Janet. "Connections or Symbols: A Dispute on the Foundations of Cognitive Science." Contemporary Psychology: A Journal of Reviews 35, no. 7 (1990): 646–48. http://dx.doi.org/10.1037/028790.

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46

Yildirir, Hasene Esra. "Secondary School Students’ Initial and Changes in Cognitive Structures of Argument and Related Concepts." International Journal of Research in Education and Science 6, no. 2 (2020): 231. http://dx.doi.org/10.46328/ijres.v6i2.859.

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The purpose of this study was to determine the state of secondary school students’ cognitive structures about argument and related concepts and to reveal the change in their cognitive structures regarding these concepts after the implementation of the argumentation-oriented approach in science lessons. This study was conducted in Grade 6, 7, 8 classes, including a total of 80 students. This study follows a pre-experimental one group pretest–posttest design. Students were administered a word association test (WAT) covering argument and related concepts prior to and following the lessons. The re

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47

Lahav, Ran. "The combinatorial-connectionist debate and the pragmatics of adjectives." Pragmatics and Cognition 1, no. 1 (1993): 71–88. http://dx.doi.org/10.1075/pc.1.1.06lah.

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Within the controversy between the combinatorial and the connectionist approaches to cognition it has been argued that our semantic and syntactic capacities provide evidence for the combinatorial approach. In this paper I offer a counter-weight to this argument by pointing out that the same type of considerations, when applied to the pragmatics of adjectives, provide evidence for connectionism.

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48

Khasanov, Rustam. "Analytical thinking as a problem of the connectionist approach in cognitive science." Artificial societies 15, no. 3 (2020): 0. http://dx.doi.org/10.18254/s207751800011011-1.

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Sharkey, Noel E., Amanda J. C. Sharkey, and Stuart A. Jackson. "Opening the black box of connectionist nets: Some lessons from cognitive science." Computer Standards & Interfaces 16, no. 3 (1994): 279–93. http://dx.doi.org/10.1016/0920-5489(94)90018-3.

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50

Wendelken, Carter, and Lokendra Shastri. "Connectionist mechanisms for cognitive control." Neurocomputing 65-66 (June 2005): 663–72. http://dx.doi.org/10.1016/j.neucom.2004.10.095.

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