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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.
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?
Rethinking Innateness asks the question, "What does it really mean to say that a behavior is innate?" The authors describe a new framework in which interactions, occurring at all levels, give rise to emergent forms and behaviors. These outcomes often may be highly constrained and universal, yet are not themselves directly contained in the genes in any domain-specific way. One of the key contributions of Rethinking Innateness is a taxonomy of ways in which a behavior can be innate. These include constraints at the level of representation, architecture, and timing; typically, behaviors arise through the interaction of constraints at several of these levels.The ideas are explored through dynamic models inspired by a new kind of "developmental connectionism," a marriage of connectionist models and developmental neurobiology, forming a new theoretical framework for the study of behavioral development. While relying heavily on the conceptual and computational tools provided by connectionism, Rethinking Innateness also identifies ways in which these tools need to be enriched by closer attention to biology.
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.
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.
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.
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.
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