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Connectionist Models

by James L. McClelland, Axel Cleeremans - OXFORD COMPANION TO CONSCIOUSNESS , 2009
"... Connectionist models, also known as Parallel Distributed Processing (PDP) models, are a class of computational models often used to model aspects of human perception, cognition, and behaviour, the learning processes underlying such behaviour, and the storage and retrieval of information from memory. ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
Connectionist models, also known as Parallel Distributed Processing (PDP) models, are a class of computational models often used to model aspects of human perception, cognition, and behaviour, the learning processes underlying such behaviour, and the storage and retrieval of information from memory

On connectionist models

by Su-youn Hong, Tag Gon Kim , 1987
"... The DEVS formalism supports modeling of discrete event systems in a hierarchical, modular manner based on the ob-ject-oriented world view. System modeling requires not only understanding of modeling framework but also domain kno-wledge of the system. Therefore, successful modeling may need a means t ..."
Abstract - Cited by 34 (3 self) - Add to MetaCart
The DEVS formalism supports modeling of discrete event systems in a hierarchical, modular manner based on the ob-ject-oriented world view. System modeling requires not only understanding of modeling framework but also domain kno-wledge of the system. Therefore, successful modeling may need a means

Biological constraints on connectionist modelling

by Simon J. Thorpe, Michel Imbert - Connectionism in Perspective , 1989
"... Many researchers interested in connectionist models accept that such models are "neurally inspired " but do not worry too much about whether their models are biologically realistic. While such a position may be perfectly justifiable, the present paper attempts to illustrate how bio ..."
Abstract - Cited by 90 (11 self) - Add to MetaCart
Many researchers interested in connectionist models accept that such models are "neurally inspired " but do not worry too much about whether their models are biologically realistic. While such a position may be perfectly justifiable, the present paper attempts to illustrate how

Connectionist models of development

by Yuko Munakata, James L. McClelland , 2003
"... How have connectionist models informed the study of development? This paper considers three contributions from specific models. First, connectionist models have proven useful for exploring nonlinear dynamics and emergent properties, and their role in nonlinear developmental trajectories, critical pe ..."
Abstract - Cited by 47 (5 self) - Add to MetaCart
How have connectionist models informed the study of development? This paper considers three contributions from specific models. First, connectionist models have proven useful for exploring nonlinear dynamics and emergent properties, and their role in nonlinear developmental trajectories, critical

Shortlist: a connectionist model of continuous speech recognition

by Dennis Norris - Cognition , 1994
"... Previous work has shown how a back-propagation network with recurrent connections can successfully model many aspects of human spoken word recogni-tion (Norris, 1988, 1990, 1992, 1993). However, such networks are unable to revise their decisions in the light of subsequent context. TRACE (McClelland ..."
Abstract - Cited by 324 (14 self) - Add to MetaCart
Previous work has shown how a back-propagation network with recurrent connections can successfully model many aspects of human spoken word recogni-tion (Norris, 1988, 1990, 1992, 1993). However, such networks are unable to revise their decisions in the light of subsequent context. TRACE (Mc

Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory

by James L. McClelland, Bruce L. McNaughton, Randall C. O'Reilly , 1995
"... Damage to the hippocampal system disrupts recent memory but leaves remote memory intact. The account presented here suggests that memories are first stored via synaptic changes in the hippocampal system, that these changes support reinstatement of recent memories in the neocortex, that neocortical s ..."
Abstract - Cited by 675 (39 self) - Add to MetaCart
synapses change a little on each reinstatement, and that remote memory is based on accumulated neocortical changes. Models that learn via changes to connections help explain this organization. These models discover the structure in ensembles of items if learning of each item is gradual and interleaved

Connectionist Models of Language Processing

by Douglas L. T. Rohde, David C. Plaut - COGN. STUD , 2003
"... Traditional approaches to language processing have been based on explicit, discrete representations which are difficult to learn from a reasonable linguistic environment—hence, it has come to be accepted that much of our linguistic representations and knowledge is innate. With its focus on learning ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
based upon graded, malleable, distributed representations, connectionist modeling has reopened the question of what could be learned from the environment in the absence of detailed innate knowledge. This paper provides an overview of connectionist models of language processing, at both the lexical

Connectionist Models in Developmental Cognitive . . .

by Mark S. Seidenberg, Jason D. Zevin
"... Connectionist models have made significant contributions to understanding developmental phenomena, mainly by providing novel computational accounts of behavioral emergence and change. What is the fate of such models given the increasing interest in and information about the biological bases of devel ..."
Abstract - Cited by 16 (0 self) - Add to MetaCart
Connectionist models have made significant contributions to understanding developmental phenomena, mainly by providing novel computational accounts of behavioral emergence and change. What is the fate of such models given the increasing interest in and information about the biological bases

Time in Connectionist Models

by Jean-Cedric Chappelier, Marco Gori, Alain Grumbach - Sequence Learning: Paradigms, Algorithms, and Applications , 2001
"... Introduction The prototypical use of "classical" connectionist models (including the multilayer perceptron (MLP), the Hopfield network and the Kohonen self-organizing map) concerns static data processing. These classical models are not well suited to working with data varying over time. I ..."
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Introduction The prototypical use of "classical" connectionist models (including the multilayer perceptron (MLP), the Hopfield network and the Kohonen self-organizing map) concerns static data processing. These classical models are not well suited to working with data varying over time

Time in connectionist models

by Marco Gori, Alain Grumbach - Sequence Learning: Paradigms, Algorithms, and Applications , 2001
"... The prototypical use of “classical ” connectionist models (including the multilayer perceptron (MLP), the Hopfield network and the Kohonen self-organizing map) concerns static data processing. These classical models are not well suited to working with data varying over time. In response to this, tem ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
The prototypical use of “classical ” connectionist models (including the multilayer perceptron (MLP), the Hopfield network and the Kohonen self-organizing map) concerns static data processing. These classical models are not well suited to working with data varying over time. In response to this
Results 1 - 10 of 1,857