Download or read book Connectionist Approaches to Language Learning written by David Touretzky and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Learning in Natural and Connectionist Systems written by R.H. Phaf and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Analogical Connections written by Keith James Holyoak and published by Intellect (UK). This book was released on 1994 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting research on the computational abilities of connectionist, neural, and neurally inspired systems, this series emphasizes the question of how connectionist or neural network models can be made to perform rapid, short-term types of computation that are useful in higher level cognitive processes. The most recent volumes are directed mainly at researchers in connectionism, analogy, metaphor, and case-based reasoning, but are also suitable for graduate courses in those areas.
Download or read book Neural Network Design and the Complexity of Learning written by J. Stephen Judd and published by MIT Press. This book was released on 1990 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neural networks and explores how certain design principles will or will not make the problems easier.Judd looks beyond the scope of any one particular learning rule, at a level above the details of neurons. There he finds new issues that arise when great numbers of neurons are employed and he offers fresh insights into design principles that could guide the construction of artificial and biological neural networks.The first part of the book describes the motivations and goals of the study and relates them to current scientific theory. It provides an overview of the major ideas, formulates the general learning problem with an eye to the computational complexity of the task, reviews current theory on learning, relates the book's model of learning to other models outside the connectionist paradigm, and sets out to examine scale-up issues in connectionist learning.Later chapters prove the intractability of the general case of memorizing in networks, elaborate on implications of this intractability and point out several corollaries applying to various special subcases. Judd refines the distinctive characteristics of the difficulties with families of shallow networks, addresses concerns about the ability of neural networks to generalize, and summarizes the results, implications, and possible extensions of the work. Neural Network Design and the Complexity of Learning is included in the Network Modeling and Connectionism series edited by Jeffrey Elman.
Download or read book Connectionist Learning written by David E. Rumelhart and published by Morgan Kaufmann Pub. This book was released on 1993-06-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains what connectionist learning is and how it relates to artificial intelligence. Develops a respresentation of knowledge and a representation of a simple computational system, and gives some examples of how such a system might work.
Download or read book Algorithmic Learning Theory II written by Setsuo Arikawa and published by IOS Press. This book was released on 1992 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Connectionist Symbol Processing written by Geoffrey E. Hinton and published by Bradford Books. This book was released on 1991 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Addressing the current tension within the artificial intelligence community betweenadvocates of powerful symbolic representations that lack efficient learning procedures and advocatesof relatively simple learning procedures that lack the ability to represent complex structureseffectively.
Download or read book Evolving Connectionist Systems written by Nikola K. Kasabov and published by Springer Science & Business Media. This book was released on 2007-08-23 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of the must-read work in the field presents generic computational models and techniques that can be used for the development of evolving, adaptive modeling systems, as well as new trends including computational neuro-genetic modeling and quantum information processing related to evolving systems. New applications, such as autonomous robots, adaptive artificial life systems and adaptive decision support systems are also covered.
Download or read book Recruitment Learning written by Joachim Diederich and published by Springer. This book was released on 2010-11-30 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a fascinating and self-contained account of "recruitment learning", a model and theory of fast learning in the neocortex. In contrast to the more common attractor network paradigm for long- and short-term memory, recruitment learning focuses on one-shot learning or "chunking" of arbitrary feature conjunctions that co-occur in single presentations. The book starts with a comprehensive review of the historic background of recruitment learning, putting special emphasis on the ground-breaking work of D.O. Hebb, W.A.Wickelgren, J.A.Feldman, L.G.Valiant, and L. Shastri. Afterwards a thorough mathematical analysis of the model is presented which shows that recruitment is indeed a plausible mechanism of memory formation in the neocortex. A third part extends the main concepts towards state-of-the-art spiking neuron models and dynamic synchronization as a tentative solution of the binding problem. The book further discusses the possible role of adult neurogenesis for recruitment. These recent developments put the theory of recruitment learning at the forefront of research on biologically inspired memory models and make the book an important and timely contribution to the field.
Download or read book Connectionist Modelling in Cognitive Neuropsychology written by David C. Plaut and published by Psychology Press. This book was released on 1994 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title presents the most comprehensive existing "case study" of how the effects of damage in connectionist models can replicate the patterns of cognitive impairments that can arise in humans as a result of brain damage.
Download or read book The Cambridge Handbook of Computational Psychology written by Ron Sun and published by Cambridge University Press. This book was released on 2008-04-28 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.
Download or read book Connectionist Models of Development written by Philip T. Quinlan and published by Psychology Press. This book was released on 2004-03-01 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book A Connectionist Model of Instructed Learning written by David Charles Noelle and published by . This book was released on 1997 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Connectionist Models of Cognition and Perception written by John Andrew Bullinaria and published by World Scientific. This book was released on 2002 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist Models of Cognition and Perception collects together refereed versions of twenty-three papers presented at the Seventh Neural Computation and Psychology Workshop (NCPW7). This workshop series is a well-established and unique forum that brings together researchers from such diverse disciplines as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their latest work on connectionist modelling in psychology.The articles have the main theme of connectionist modelling of cognition and perception, and are organised into six sections, on: cell assemblies, representation, memory, perception, vision and language. This book is an invaluable resource for researchers interested in neural models of psychological phenomena.
Download or read book From Learning Theory to Connectionist Theory written by William Kaye Estes and published by Psychology Press. This book was released on 1992 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Connectionism and Psychology written by Philip T. Quinlan and published by University of Chicago Press. This book was released on 1991 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid growth of neural network research has led to a major reappraisal of many fundamental assumptions in cognitive and perceptual psychology. This text—aimed at the advanced undergraduate and beginning postgraduate student—is an in-depth guide to those aspects of neural network research that are of direct relevance to human information processing. Examples of new connectionist models of learning, vision, language and thought are described in detail. Both neurological and psychological considerations are used in assessing its theoretical contributions. The status of the basic predicates like exclusive-OR is examined, the limitations of perceptrons are explained and properties of multi-layer networks are described in terms of many examples of psychological processes. The history of neural networks is discussed from a psychological perspective which examines why certain issues have become important. The book ends with a general critique of the new connectionist approach. It is clear that new connectionism work provides a distinctive framework for thinking about central questions in cognition and perception. This new textbook provides a clear and useful introduction to its theories and applications.
Download or read book From Learning Theory to Connectionist Theory written by Alice F. Healy and published by Psychology Press. This book was released on 1992 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1992. Routledge is an imprint of Taylor & Francis, an informa company.
