Learning In Natural And Connectionist Systems
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Learning In Natural And Connectionist Systems
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Author : R.H. Phaf
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Learning In Natural And Connectionist Systems written by R.H. Phaf and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
Modern research in neural networks has led to powerful artificial learning systems, while recent work in the psychology of human memory has revealed much about how natural systems really learn, including the role of unconscious, implicit, memory processes. Regrettably, the two approaches typically ignore each other. This book, combining the approaches, should contribute to their mutual benefit. New empirical work is presented showing dissociations between implicit and explicit memory performance. Recently proposed explanations for such data lead to a new connectionist learning procedure: CALM (Categorizing and Learning Module), which can learn with or without supervision, and shows practical advantages over many existing procedures. Specific experiments are simulated by a network model (ELAN) composed of CALM modules. A working memory extension to the model is also discussed that could give it symbol manipulation abilities. The book will be of interest to memory psychologists and connectionists, as well as to cognitive scientists who in the past have tended to restrict themselves to symbolic models.
Learning In Natural And Connectionist Systems
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Author : Rutger Hans Phaf
language : en
Publisher:
Release Date : 1991
Learning In Natural And Connectionist Systems written by Rutger Hans Phaf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with categories.
Connectionist Natural Language Processing
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Author : Noel Sharkey
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Connectionist Natural Language Processing written by Noel Sharkey and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Language Arts & Disciplines categories.
Connection science is a new information-processing paradigm which attempts to imitate the architecture and process of the brain, and brings together researchers from disciplines as diverse as computer science, physics, psychology, philosophy, linguistics, biology, engineering, neuroscience and AI. Work in Connectionist Natural Language Processing (CNLP) is now expanding rapidly, yet much of the work is still only available in journals, some of them quite obscure. To make this research more accessible this book brings together an important and comprehensive set of articles from the journal CONNECTION SCIENCE which represent the state of the art in Connectionist natural language processing; from speech recognition to discourse comprehension. While it is quintessentially Connectionist, it also deals with hybrid systems, and will be of interest to both theoreticians as well as computer modellers. Range of topics covered: Connectionism and Cognitive Linguistics Motion, Chomsky's Government-binding Theory Syntactic Transformations on Distributed Representations Syntactic Neural Networks A Hybrid Symbolic/Connectionist Model for Understanding of Nouns Connectionism and Determinism in a Syntactic Parser Context Free Grammar Recognition Script Recognition with Hierarchical Feature Maps Attention Mechanisms in Language Script-Based Story Processing A Connectionist Account of Similarity in Vowel Harmony Learning Distributed Representations Connectionist Language Users Representation and Recognition of Temporal Patterns A Hybrid Model of Script Generation Networks that Learn about Phonological Features Pronunciation in Text-to-Speech Systems
Connectionist Symbolic Integration
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Author : Ron Sun
language : en
Publisher: Psychology Press
Release Date : 2013-04-15
Connectionist Symbolic Integration written by Ron Sun and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-15 with Psychology categories.
A variety of ideas, approaches, and techniques exist -- in terms of both architecture and learning -- and this abundance seems to lead to many exciting possibilities in terms of theoretical advances and application potentials. Despite the apparent diversity, there is clearly an underlying unifying theme: architectures that bring together symbolic and connectionist models to achieve a synthesis and synergy of the two different paradigms, and the learning and knowledge acquisition methods for developing such architectures. More effort needs to be extended to exploit the possibilities and opportunities in this area. This book is the outgrowth of The IJCAI Workshop on Connectionist-Symbolic Integration: From Unified to Hybrid Approaches, held in conjunction with the fourteenth International Joint Conference on Artificial Intelligence (IJCAI '95). Featuring various presentations and discussions, this two-day workshop brought to light many new ideas, controversies, and syntheses which lead to the present volume. This book is concerned with the development, analysis, and application of hybrid connectionist-symbolic models in artificial intelligence and cognitive science. Drawing contributions from a large international group of experts, it describes and compares a variety of models in this area. The types of models discussed cover a wide range of the evolving spectrum of hybrid models, thus serving as a well-balanced progress report on the state of the art. As such, this volume provides an information clearinghouse for various proposed approaches and models that share the common belief that connectionist and symbolic models can be usefully combined and integrated, and such integration may lead to significant advances in understanding intelligence.
Connectionist Models Of Neurons Learning Processes And Artificial Intelligence
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Author : Jose Mira
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-06-05
Connectionist Models Of Neurons Learning Processes And Artificial Intelligence written by Jose Mira and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-06-05 with Computers categories.
This book constitutes, together with its companion, LNCS 2085, the refereed proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, held in Granada, Spain, in June 2001. The 200 revised papers presented were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in sections on foundations of connectionism, biophysical models of neurons, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, artificial intelligence and congnitive processes, methodology for nets design, nets simulation and implementation, bio-inspired systems and engineering, and other applications in a variety of fields.
Current Trends In Connectionism
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Author : Lars F. Niklasson
language : en
Publisher: Psychology Press
Release Date : 2013-07-04
Current Trends In Connectionism written by Lars F. Niklasson and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-04 with Psychology categories.
In order to build "intelligent" machines, many researchers have turned to the only naturally occurring intelligent system: the brain. For quite a while now, both the function and architecture of the brain have served as inspiration to philosophers, psychologists, computer scientists, neurobiologists, physicists and others in their quest for solving problems that seem to require intelligence in their own particular domain. The progress in the field of connectionism -- or artificial neural networks -- has had its ups and downs during its maturing years. Advocates of the field pointed out the virtues of connectionist systems, dealing with low-level cognitive tasks such as visual recognition and pattern completion, and inherent properties such as generalization, fault tolerance and parallel processing. However, research in the field virtually came to a halt at the end of the 1960s when Minsky and Papert published their critical analysis of connectionist systems, Perceptrons. In the beginning of the 1980s, the field was reborn with the appearance of new powerful learning methods which overcame many of the computational problems identified by Minsky and Papert. This volume is characterized by a number of different research directions distinguished by their perspectives on systems comprising interconnected sets of simple processing elements. Scientists who have strong backgrounds in neurobiology concentrate on the issues involved when modelling natural systems. Researchers with philosophical and psychological backgrounds stress other aspects which might not always be intuitively relevant to biology but instead are concerned with the mind and its higher-order cognitive capabilities. On the other hand, many researchers and engineers in industry take advantage of the wide applicability and mathematical properties of connectionist systems in order to solve practical problems, sacrificing even more of the principles underlying the basic idea of mimicking the function and architecture of the brain. None of these directions are right or wrong, but there has perhaps been too little exchange of knowledge and experience between them. The main purpose for organizing this conference was to bring together researchers with different backgrounds to exchange ideas and visions in the broad field of connectionism -- providing means for new insights that may push this area to another major breakthrough.
Connectionist Approaches To Language Learning
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Author : David Touretzky
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Connectionist Approaches To Language Learning written by David Touretzky and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
arise automatically as a result of the recursive structure of the task and the continuous nature of the SRN's state space. Elman also introduces a new graphical technique for study ing network behavior based on principal components analysis. He shows that sentences with multiple levels of embedding produce state space trajectories with an intriguing self similar structure. The development and shape of a recurrent network's state space is the subject of Pollack's paper, the most provocative in this collection. Pollack looks more closely at a connectionist network as a continuous dynamical system. He describes a new type of machine learning phenomenon: induction by phase transition. He then shows that under certain conditions, the state space created by these machines can have a fractal or chaotic structure, with a potentially infinite number of states. This is graphically illustrated using a higher-order recurrent network trained to recognize various regular languages over binary strings. Finally, Pollack suggests that it might be possible to exploit the fractal dynamics of these systems to achieve a generative capacity beyond that of finite-state machines.
The Symbolic And Connectionist Paradigms
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Author : John Dinsmore
language : en
Publisher: Psychology Press
Release Date : 2014-01-14
The Symbolic And Connectionist Paradigms written by John Dinsmore and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-14 with Psychology categories.
The modern study of cognition finds itself with two widely endorsed but seemingly incongruous theoretical paradigms. The first of these, inspired by formal logic and the digital computer, sees reasoning in the principled manipulation of structured symbolic representations. The second, inspired by the physiology of the brain, sees reasoning as the behavior that emerges from the direct interactions found in large networks of simple processing components. Each paradigm has its own accomplishments, problems, methodology, proponents, and agenda. This book records the thoughts of researchers -- from both computer science and philosophy -- on resolving the debate between the symbolic and connectionist paradigms. It addresses theoretical and methodological issues throughout, but at the same time exhibits the current attempts of practicing cognitive scientists to solve real problems.
Hybrid Neural Systems
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Author : Stefan Wermter
language : en
Publisher: Springer
Release Date : 2006-12-30
Hybrid Neural Systems written by Stefan Wermter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-30 with Medical categories.
Hybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS'98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems. The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches.
Connectionist Models Of Development
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Author : Philip T. Quinlan
language : en
Publisher: Psychology Press
Release Date : 2003-05-22
Connectionist Models Of Development written by Philip T. Quinlan and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-22 with Psychology categories.
Connectionist Models of Development is an edited collection of essays on the current work concerning connectionist or neural network models of human development. The brain comprises millions of nerve cells that share myriad connections, and this book looks at how human development in these systems is typically characterised as adaptive changes to the strengths of these connections. The traditional accounts of connectionist learning, based on adaptive changes to weighted connections, are explored alongside the dynamic accounts in which networks generate their own structures as learning proceeds. Unlike most connectionist accounts of psychological processes which deal with the fully-mature system, this text brings to the fore a discussion of developmental processes. To investigate human cognitive and perceptual development, connectionist models of learning and representation are adopted alongside various aspects of language and knowledge acquisition. There are sections on artificial intelligence and how computer programs have been designed to mimic the development processes, as well as chapters which describe what is currently known about how real brains develop. This book is a much-needed addition to the existing literature on connectionist development as it includes up-to-date examples of research on current controversies in the field as well as new features such as genetic connectionism and biological theories of the brain. It will be invaluable to academic researchers, post-graduates and undergraduates in developmental psychology and those researching connectionist/neural networks as well as those in related fields such as psycholinguistics.