Layered Hybrid Connectionist Models for Cognitive Science

2000 ◽  
pp. 14-27 ◽  
Author(s):  
Jerome Feldman ◽  
David Bailey
Keyword(s):  
Cognitive Science ◽  
Connectionist Models

scholarly journals Folk psychology, eliminativism, and the present state of connectionism

2021 ◽  
Vol 64 (1) ◽  
pp. 173-196
Author(s):  
Vanja Subotic
Keyword(s):  
Cognitive Science ◽  
Cognitive Processing ◽  
Folk Psychology ◽  
Short Term Memory ◽  
Distributed Processing ◽  
Cognitive Architecture ◽  
Propositional Attitudes ◽  
Connectionist Models ◽  
Short Term ◽  
Long Short Term Memory

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 radical opponent of folk psychology and a prominent supporter of eliminative materialism. I aim to examine whether current connectionist models based on long-short term memory (LSTM) neural networks can back up these arguments in favor of eliminativism. Nonetheless, I will rather put my faith in the eliminativism of the limited domain. This position amount to the following claim: even though that connectionist cognitive science has no need whatsoever for folk psychology qua theory, this does not entail illegitimacy of folk psychology per se in other scientific domains, most notably in humanities, but only if one sees folk psychology as mere heuristics.

Connectionism and Universals of Second Language Acquisition

1990 ◽  
Vol 12 (2) ◽  
pp. 179-199 ◽  
Author(s):  
Michael Gasser
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Acquisition ◽  
Cognitive Science ◽  
First Language ◽  
Language Theory ◽  
Connectionist Models ◽  
Language Patterns ◽  
Simple Processing ◽  
Constituent Order

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 acquisition can be tested. Inputs and outputs are patterns of activation on units representing both form and meaning. Learning consists of the unsupervised association of pattern elements with one another. A network is first trained on a set of first language patterns and then exposed to a set of second language patterns with the same meanings. Several simulations of constituent-order transfer within this framework are discussed.

Resisting the tyranny of terminology: The general dynamical hypothesis in cognitive science

1998 ◽  
Vol 21 (5) ◽  
pp. 643-643
Author(s):  
Terence Horgan ◽  
John Tienson
Keyword(s):  
Cognitive Science ◽  
Connectionist Models ◽  
Dynamical Hypothesis ◽  
Special Case

What van Gelder calls the dynamical hypothesis is only a special case of what we here dub the general dynamical hypothesis. His terminology makes it easy to overlook important alternative dynamical approaches in cognitive science. Connectionist models typically conform to the general dynamical hypothesis, but not to van Gelder's.

scholarly journals El estudio neurológico de la conciencia: una valoración crítica

2015 ◽  
Vol 32 (1) ◽  
pp. 266
Author(s):  
José M. Zumalabe-Makirriain
Keyword(s):  
Nervous System ◽  
Computational Model ◽  
Cognitive Science ◽  
Critical Perspective ◽  
Connectionist Models ◽  
Causal Relations ◽  
Computational Paradigm ◽  
The Brain

During the predominance, in the cognitive science, of the classic symbolic-computational paradigm hardly was paid attention to the neurobiological study of the consciousness. With the appearance of the connectionist models which start of a more naturalized and less abiologic conception of the psychology, was taken a radical turn in this subject. Since this current the explanation of the mental phenomenons needs to include references to the biological support because is taken like a computational model the running of the nervous system. After describing the works of the neuroscientist about the neuronal correlates on the consciousness, we analyze since a critical perspective, the limitations and the weaknesses of them refered basically to the conceptual troubles of the connectionism, to the objections to the localizacionism, to the limitations of the cerebral image techniques, to the lack of stablishment of the brain-mind causal relations and to the exclusivist and reductionist pretension of the most part of the investigations.

scholarly journals The exploratory status of postconnectionist models

2020 ◽  
Vol 63 (2) ◽  
pp. 135-164
Author(s):  
Miljana Milojevic ◽  
Vanja Subotic
Keyword(s):  
Cognitive Science ◽  
Neural Nets ◽  
Human Cognition ◽  
Connectionist Models ◽  
Learning Techniques ◽  
History Of ◽  
Alternative Methodology ◽  
Connectionist Approach ◽  
Sharp Criticism

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. Criticisms have mostly pointed to its explanatory inadequacy as a theory of cognition or to its biological implausibility as a theory of implementation, and critics often focused on specific shortcomings of some connectionist models and argued that they apply on connectionism in general. In this paper we want to show that both types of critique are based on the assumption that the only valid explanations in cognitive science are instances of homuncular functionalism and that by removing this assumption and by adopting an alternative methodology - exploratory mechanistic strategy, we can reject most objections to connectionism as irrelevant, explain the progress of connectionist models despite their shortcomings and sketch the trajectory of their future development. By adopting mechanistic explanations and by criticizing functionalism, we will reject the objections of explanatory inadequacy, by characterizing connectionist models as generic rather than concrete mechanisms, we will reject the objections of biological implausibility, and by attributing the exploratory character to connectionist models we will show that practice of generalizing current to general failures of connectionism is unjustified.

Bring ART into the ACT

2003 ◽  
Vol 26 (5) ◽  
pp. 610-611 ◽  
Author(s):  
Stephen Grossberg
Keyword(s):  
Cognitive Science ◽  
Real Time ◽  
Adaptive Resonance Theory ◽  
Connectionist Model ◽  
Neural Models ◽  
Connectionist Models ◽  
Resonance Theory ◽  
Adaptive Resonance

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.

Connectionist Models and Cognitive Theory

1993 ◽  
Vol 4 (4) ◽  
pp. 228-235 ◽  
Author(s):  
Mark S. Seidenberg
Keyword(s):  
Cognitive Science ◽  
Cognitive Neuroscience ◽  
Simulation Modeling ◽  
Cognitive Theory ◽  
Connectionist Models ◽  
Statistical Tool ◽  
Considerable Debate ◽  
Small Set

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 principles that apply in a variety of domains. Construed in this way, it contributes to the development of theories that are explanatory, not merely descriptive.

Language as a mental travel guide

2020 ◽  
Vol 43 ◽  
Author(s):  
Charles P. Davis ◽  
Gerry T. M. Altmann ◽  
Eiling Yee
Keyword(s):  
Cognitive Science ◽  
Human Cognition ◽  
Travel Guide

Abstract Gilead et al.'s approach to human cognition places abstraction and prediction at the heart of “mental travel” under a “representational diversity” perspective that embraces foundational concepts in cognitive science. But, it gives insufficient credit to the possibility that the process of abstraction produces a gradient, and underestimates the importance of a highly influential domain in predictive cognition: language, and related, the emergence of experientially based structure through time.

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