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Covers recent research in connectionism on a range of topics from biology to hardware, and from psychology to philosophy. Topics include: the mind-body problem, neural networks and computing, cognition and non-linear dynamics, language learning and neurobiology.
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
The latest title in the Cognitive Science and Second Language Acquisition Series presents a comprehensive review of connectionist research in second language acquisition (SLA). Second language researchers and the cognitive science community will find accessible discussions of the relevance of connectionist research to SLA. This important volume is key reading for any student or researcher interested in how second language acquisition can be better understood from a connectionist perspective.
An evaluation of the merits, potential, and limits of Connectionism, this book also illustrates current research programs and recent trends.Connectionism (also known as Neural Networks) is an exciting new field which has brought together researchers from different areas such as artificial intelligence, computer science, cognitive science, neuroscience, physics, and complex dynamics. These researchers are applying the connectionist paradigm in an interdisciplinary way to the analysis and design of intelligent systems.In this book, researchers from the above-mentioned fields not only report on their most recent research results, but also describe Connectionism from the perspective of their own field, looking at issues such as: - the effects and the utility of Connectionism for their field - the potential and limitations of Connectionism - can it be combined with other approaches?
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.
A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.
This resource defines and refines two major theoretical approaches within developmental science that address the central issues of development-connectionism and dynamical systems theory.
Setting forth the state of the art, leading researchers present a survey on the fast-developing field of Connectionist Psycholinguistics: using connectionist or neural networks, which are inspired by brain architecture, to model empirical data on human language processing. Connectionist psycholinguistics has already had a substantial impact on the study of a wide range of aspects of language processing, ranging from inflectional morphology, to word recognition, to parsing and language production. Christiansen and Chater begin with an extended tutorial overview of Connectionist Psycholinguistics which is followed by the latest research by leading figures in each area of research. The book also focuses on the implications and prospects for connectionist models of language, not just for psycholinguistics, but also for computational and linguistic perspectives on natural language. The interdisciplinary approach will be relevant for, and accessible to psychologists, cognitive scientists, linguists, philosophers, and researchers in artificial intelligence.
This volume offers an introduction to consciousness research within philosophy, psychology and neuroscience, from a philosophical perspective and with an emphasis on the history of ideas and core concepts. The book begins by examining consciousness as a modern mystery. Thereafter, the book introduces philosophy of mind and the mind-body problem, and proceeds to explore psychological, philosophical and neuroscientific approaches to mind and consciousness. The book then presents a discussion of mysterianist views of consciousness in response to what can be perceived as insurmountable scientific challenges to the problem of consciousness. As a response to mysterianist views, the next chapters examine radical approaches to rethinking the problem of consciousness, including externalist approaches. The final two chapters present the author’s personal view of the problem of consciousness. Consciousness remains a mystery for contemporary science—a mystery raising many questions. Why does consciousness persist as a mystery? Are we humans not intelligent enough to solve the riddle of consciousness? If we can solve this mystery, what would it take? What research would we need to conduct? Moreover, the mystery of consciousness prompts the larger question of how well the cognitive sciences have actually advanced our understanding of ourselves as human beings. After all, consciousness is not just a minor part of our existence. Without consciousness, we would not be human beings at all. This book aims to increase the accessibility of major ideas in the field of consciousness research and to inspire readers to contribute to the ongoing discussion of the place of consciousness in nature.
Many of our thoughts and decisions occur without us being conscious of them taking place; connectionism attempts to reveal the internal hidden dynamics that drive the thoughts and actions of both individuals and groups. Connectionist modeling is a radically innovative approach to theorising in psychology, and more recently in the field of social psychology. The connectionist perspective interprets human cognition as a dynamic and adaptive system that learns from its own direct experiences or through indirect communication from others. Social Connectionism offers an overview of the most recent theoretical developments of connectionist models in social psychology. The volume is divided into four sections, beginning with an introduction and overview of social connectionism. This is followed by chapters on causal attribution, person and group impression formation, and attitudes. Each chapter is followed by simulation exercises that can be carried out using the FIT simulation program; these guided exercises allow the reader to reproduce published results. Social Connectionism will be invaluable to graduate students and researchers primarily in the field of social psychology, but also in cognitive psychology and connectionist modeling.