Newell introduces Soar, an architecture for general cognition. A pioneer system in AI, Soar is the first problem-solver to create its own subgoals and learn continuously from its own experience. Its ability to operate within the real-time constraints of intelligent behavior illustrates important characteristics of human cognition.

It is argued in this book that there are three major approaches to anxiety. First, there is anxiety as an emotional state. Second, there is trait anxiety as a dimension of personality. Third, there is anxiety as a set of anxiety disorders. What is attempted is to produce a unified theory of anxiety which integrates all these major approaches. According to this unified theory, there are four sources of information which influence the level of experienced anxiety: (1) experimental stimulation; (2) internal physiological activity; (3) internal cognitions, (e.g., worries); and (4) one's own behaviour. The unified theory is essentially based on a cognitive approach. More specifically, it is assumed that individual differences in experienced anxiety between those high and low in trait anxiety depend largely on cognitive biases. It is also assumed that the various anxiety disorders depend on cognitive biases, and that the main anxiety disorders differ in terms of the source of information most affected by such biases (e.g., social phobics have biased interpretation of their own behaviour). In sum, this book presents a general theory of anxiety from the cognitive perspective. It is intended that this theory will influence theory and research on emotion, personality, and the anxiety disorders. Correction notice: Christos Halkiopoulos should have been credited for his role as the inventor of the Dot Probe Paradigm and for the design and execution of the experiment discussed in C. D. Spielberger, I. G. Sarason, Z. Kulczar, and J. Van Heck (Eds.), Stress and Emotion, Vol. 14. London: Hemisphere.

Soar: A Cognitive Architecture in Perspective represents a European perspective on Soar with the exception of the special contribution from Allen Newell arguing for Unified Theories of Cognition. The various papers derive from the work of the Soar Research Group that has been active at the University of Groningen, The Netherlands, since 1987. The work reported here has been inspired in particular by two topics that precipitated the group's interest in Soar in the first place -- road user behavior and the temporal organization of behavior, more specifically planning. At the same time, the various contributions go well beyond the simple use of Soar as a convenient medium for modeling human cognitive activity. In every paper one or more fundamental issues are raised that touch upon the very nature and consistency of Soar as an intelligent architecture. As a result the reader will learn about the operator implementation problem, chunking, multitasking, the need to constrain the depth of the goal stack, and induction, etc. Soar is still at a relatively early stage of development. It does, nevertheless, constitute an important breakthrough in the area of computer architectures for general intelligence. Soar shows one important direction that future efforts to build intelligent systems should take if they aim for a comprehensive, and psychologically meaningful, theory of cognition. This is argued in a powerful way by Newell in his contribution to this volume. For this reason, the Soar system will probably play an important integrative role within cognitive science in bringing together important subdomains of psychology, computer science, linguistics, and the neurosciences. Although Soar is not the only `architecture for intelligence', it is one of the most advanced and theoretically best motivated architectures presently available. Soar: A Cognitive Architecture in Perspective is of special interest to researchers in the domains of cognitive science, computer science and artificial intelligence, cognitive psychology, and the philosophy of mind.

This book presents the most important contributions to modern psychological science and explains how the contributions came to be.

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

This eagerly awaited volume presents Anderson's cumulative progress in unified social psychology. The research is grounded in the three fundamental laws of information integration theory. Research shows these laws to apply to topics in social and personality psychology such as person cognition, attitudes, moral cognition, social development, group dynamics and self-cognition. This definitive work will broaden the appreciation of Anderson's unique treatment of psychological processes.

This volume offers an overview of the philosophy of cognitive science that balances breadth and depth, with chapters covering every aspect of the psychology and cognitive anthropology.

A mechanistic theory of the representation and use of semantic knowledge that uses distributed connectionist networks as a starting point for a psychological theory of semantic cognition.

The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.

It is argued in this book that there are three major approaches to anxiety. First, there is anxiety as an emotional state. Second, there is trait anxiety as a dimension of personality. Third, there is anxiety as a set of anxiety disorders. What is attempted is to produce a unified theory of anxiety which integrates all these major approaches. According to this unified theory, there are four sources of information which influence the level of experienced anxiety: (1) experimental stimulation; (2) internal physiological activity; (3) internal cognitions, (e.g., worries); and (4) one's own behaviour. The unified theory is essentially based on a cognitive approach. More specifically, it is assumed that individual differences in experienced anxiety between those high and low in trait anxiety depend largely on cognitive biases. It is also assumed that the various anxiety disorders depend on cognitive biases, and that the main anxiety disorders differ in terms of the source of information most affected by such biases (e.g., social phobics have biased interpretation of their own behaviour). In sum, this book presents a general theory of anxiety from the cognitive perspective. It is intended that this theory will influence theory and research on emotion, personality, and the anxiety disorders. Correction notice: Christos Halkiopoulos should have been credited for his role as the inventor of the Dot Probe Paradigm and for the design and execution of the experiment discussed in C. D. Spielberger, I. G. Sarason, Z. Kulczar, and J. Van Heck (Eds.), Stress and Emotion, Vol. 14. London: Hemisphere.