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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.
Electronic Inspection Copy available to instructors here 'Since its very first edition, Social Cognition has been the undisputed bible of the field, and this new edition is the best one yet. Insightful, authoritative, and beautifully written by two of the field's most eminent researchers, it is an indispensable guide for students and scientists alike. The book that came first remains first.' -Daniel Gilbert, Harvard University, UK 'This latest edition of the best overview of social cognition research somehow succeeds in lifting the bar higher still for its competitors. It is authoritative yet readable, and has depth as well as breadth -- an irresistible invitation to the field!' - Miles Hewstone, University of Oxford, UK In Social Cognition: From Brains to Culture 2nd Edition, Fiske and Taylor carefully integrate the many new threads of social cognition research that have emerged in the intervening years since the previous edition, including developments within social neuroscience, cultural psychology and some areas of applied psychology, and continue to tell a powerful and comprehensive story about what social cognition is and why it's a significant phenomenon in society today. Every updated chapter now includes more figures and tables, glossary entries, and further readings. A supplemental test bank including some full-text journal articles corresponding to chapters in the book is available online at: www.sagepub.co.uk/fiskeandtaylor. This textbook will be indispensable to students of social cognition and social psychology worldwide, at undergraduate or graduate level. Visit the Companion Website at www.sagepub.co.uk/fiskeandtaylor
Organisms survive and succeed because of their ability to learn and adapt to changing circumstances and new demands. As discussed in the chapters of the present volume, an appreciation of the mechanisms and principles of learning and conditioning is fundamental to any analysis of normal behavior as well as to an informed understanding of our well being (including examination of such issues as anxiety and fear, brain-immune system interactions, drug addiction and abuse, emotional learning, and social behavior) and mental health (for example, autism, depression, helplessness and schizophrenia). The twenty-three chapters in this volume, written by a distinguished collection of internationally renowned scholars, articulate the basic, yet sophisticated, way in which learning and conditioning processes influence our everyday behaviors, both normal and maladaptive, and help explain a variety of clinically important phenomena and disorders.
Annotation As one of our highest expressions of thought and creativity, music has always been a difficult realm to capture, model, and understand. The connectionist paradigm, now beginning to provide insights into many realms of human behavior, offers a new and unified viewpoint from which to investigate the subtleties of musical experience. Music and Connectionism provides a fresh approach to both fields, using the techniques of connectionism and parallel distributed processing to look at a wide range of topics in music research, from pitch perception to chord fingering to composition.The contributors, leading researchers in both music psychology and neural networks, address the challenges and opportunities of musical applications of network models. The result is a current and thorough survey of the field that advances understanding of musical phenomena encompassing perception, cognition, composition, and performance, and in methods for network design and analysis.Peter M. Todd is a doctoral candidate in the PDP Research Group of the Psychology Department at Stanford University. Gareth Loy is an award-winning composer, a lecturer in the Music Department of the University of California, San Diego, and a member of the technical staff of Frox Inc.Contributors. Jamshed J. Bharucha. Peter Desain. Mark Dolson. Robert Gjerclingen. Henkjan Honing. B. Keith Jenkins. Jacqueline Jons. Douglas H. Keefe. Tuevo Kohonen. Bernice Laden. Pauli Laine. Otto Laske. Marc Leman. J. P. Lewis. Christoph Lischka. D. Gareth Loy. Ben Miller. Michael Mozer. Samir I. Sayegh. Hajime Sano. Todd Soukup. Don Scarborough. Kalev Tiits. Peter M. Todd. Kari Torkkola.
This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. One of the most, if not the most, exciting developments within cognitive science has been the emergence of connectionism as an alternative to the computational conception of the mind that tends to dominate the discipline. In this volume, John Tienson and Terence Horgan have brought together a fine collection of stimulating studies on connectionism and its significance. As the Introduction explains, the most pressing questions concern whether or not connectionism can provide a new conception of the nature of mentality. By focusing on the similarities and differences between connectionism and other approaches to cognitive science, the chapters of this book supply valuable resources that advance our understanding of these difficult issues. J.H.F.
The social sciences, especially economics, management, and organizational science, are experiencing a tremendous renewed interest for their epistemological and methodological statutes, as witnessed by the many books and specialized journals established during the last two decades. Relational Methodologies and Epistemology in the Economics and Management Sciences identifies and presents the four main network-based methodologies including network analysis, Boolean network simulation modeling, artificial neural network simulation modeling, and agent-based simulation modeling in addition to their conceptual-epistemological implications and concrete applications within the social and natural sciences. Featuring a critical assessment of relational methodologies and their practical applications, this timely publication is ideal for use by corporate R&D departments, researchers, theorists, and graduate-level students.
The issues raised by the role of language in education are some of the most important and contentious faced by education systems across the globe. Language is embedded in the concepts of nationhood and identity, and is therefore directly linked to the very social and political fabric of a country. In a climate of increasing globalisation, development and mobility of populations, nations around the world are concerned with the tension between cultivating a sense of cultural and linguistic cohesion and making use of the linguistic diversity that exists in every country and region. This book examines the implications and impacts, the dilemmas and potential for language education in relation to education systems and wider society. Split into three key parts, it considers: *current issues in language education, including the role of language in maintaining power and inequalities, in encouraging participation and inclusion and in challenging the status quo; *different approaches to language education around the world; *the potential for language to provide opportunities for the disadvantaged, illustrated by case studies of three cities. This recent volume of the internationally respected World Yearbook of Education continues the tradition of offering a wide range of international perspectives from leading commentators on a universal concern. The material amassed here will be essential reading for teacher educators, education researchers and school leaders across the world.
This publication reflects on the discussion on using chaos theory for the study of society. It explores the interface between chaos theory and the social sciences. A broad variety of fields (including Sociology, Anthropology, Economics, Political Science, Management, Philosophy and Cognitive Sciences) is represented in the book. The leading themes are: Conceptual and Methodological Issues, Social Connectionism and the Connectionist Mind, Social Institutions and Public Policy, and Social Simulations. The book includes the following topics: the relevance of the complexity-chaos paradigm for analyzing social systems, the usefulness of nonlinear dynamics for studying the formation and sustainability of social groups, the comparison between spontaneous social orders and spontaneous biological/natural orders, the building of Artificial Societies, and the contribution of the chaos paradigm to a better understanding and formulation of public policies.
Cognitive Neuroscience and Psychotherapy provides a bionetwork theory unifying empirical evidence in cognitive neuroscience and psychopathology to explain how emotion, learning, and reinforcement affect personality and its extremes. The book uses the theory to explain research results in both disciplines and to predict future findings, as well as to suggest what the theory and evidence say about how we should be treating disorders for maximum effectiveness. While theoretical in nature, the book has practical applications, and takes a mathematical approach to proving its own theorems. The book is unapologetically physical in nature, describing everything we think and feel by way of physical mechanisms and reactions in the brain. This unique marrying of cognitive neuroscience and clinical psychology provides an opportunity to better understand both. - Unifying theory for cognitive neuroscience and clinical psychology - Describes the brain in physical terms via mechanistic processes - Systematically uses the theory to explain empirical evidence in both disciplines - Theory has practical applications for psychotherapy - Ancillary material may be found at: http://booksite.elsevier.com/9780124200715 including an additional chapter and supplements
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.