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Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Psychology Workshop - the only international workshop devoted to connectionist models of psychological phenomena. With a main theme of neural network modelling in the areas of evolution, learning, and development, the papers are organized into six sections: The neural basis of cognition Development and category learning Implicit learning Social cognition Evolution Semantics Covering artificial intelligence, mathematics, psychology, neurobiology, and philosophy, it will be an invaluable reference work for researchers and students working on connectionist modelling in computer science and psychology, or in any area related to cognitive science.
A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.
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.
The neural computational approach to cognitive and psychological processes is relatively new. However, Neural Computation and Psychology Workshops (NCPW), first held 16 years ago, lie at the heart of this fast-moving discipline, thanks to its interdisciplinary nature — bringing together researchers from different disciplines such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their work on models of cognitive processes.Once again, the Eleventh Neural Computation and Psychology Workshop (NCPW11), held in 2008 at the University of Oxford (England), reflects the interdisciplinary nature and wide range of backgrounds of this field. This volume is a collection of peer-reviewed contributions of most of the papers presented at NCPW11 by researchers from four continents and 15 countries.
Vol. includes all papers and posters presented at 2001 Cog Sci Mtg & summaries of symposia & invited addresses. Deals w/ issues of repres & model'g cog processes. Appeals to scholars in subdisciplines that comprise Cog Sci: Psych, Computr Sci, Neuro, Lin
The neural computational approach to cognitive and psychological processes is relatively new. However, Neural Computation and Psychology Workshops (NCPW), first held 16 years ago, lie at the heart of this fast-moving discipline, thanks to its interdisciplinary nature ? bringing together researchers from different disciplines such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their work on models of cognitive processes.Once again, the Eleventh Neural Computation and Psychology Workshop (NCPW11), held in 2008 at the University of Oxford (England), reflects the interdisciplinary nature and wide range of backgrounds of this field. This volume is a collection of peer-reviewed contributions of most of the papers presented at NCPW11 by researchers from four continents and 15 countries.
Connectionism and the Mind provides a clear and balanced introduction to connectionist networks and explores theoretical and philosophical implications. Much of this discussion from the first edition has been updated, and three new chapters have been added on the relation of connectionism to recent work on dynamical systems theory, artificial life, and cognitive neuroscience. Read two of the sample chapters on line: Connectionism and the Dynamical Approach to Cognition: http://www.blackwellpublishing.com/pdf/bechtel.pdf Networks, Robots, and Artificial Life: http://www.blackwellpublishing.com/pdf/bechtel2.pdf
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.
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.
Bringing together contributions in biology, neuroscience, computer science, physics, and psychology, this book offers a solid tutorial on current research activity in connectionist-inspired biology-based modeling. It describes specific experimental approaches and also confronts general issues related to learning associative memory, and sensorimotor development. Introductory chapters by editors Hanson and Olson, along with Terrence Sejnowski, Christof Koch, and Patricia S. Churchland, provide an overview of computational neuroscience, establish the distinction between "realistic" brain models and "simplified" brain models, provide specific examples of each, and explain why each approach might be appropriate in a given context. The remaining chapters are organized so that material on the anatomy and physiology of a specific part of the brain precedes the presentation of modeling studies. The modeling itself ranges from simplified models to more realistic models and provides examples of constraints arising from known brain detail as well as choices modelers face when including or excluding such constraints. There are three sections, each focused on a key area where biology and models have converged. Stephen Jose Hanson is Member of Technical Staff, Bellcore, and Visiting Faculty, Cognitive Science Laboratory, Princeton University. Carl R. Olson is Assistant Professor, Department of Psychology at Princeton Connectionist Modeling and Brain Functionis included in the Network Modeling and Connectionism series, edited by Jeffrey Elman.