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Oxford Series on Cognitive Models and Architectures Ser.: Principles of Synthetic Intelligence : Psi: an Architecture of Motivated Cognition by Joscha Bach (2009, Hardcover)

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These drives routinely influence goal formation and knowledge selection and application. The sweep of the architecture can thus be larger-it presents a new cognitive architecture attempting to provide a unified theory of cognition.

About this product

Product Identifiers

PublisherOxford University Press, Incorporated

ISBN-100195370678

ISBN-139780195370676

eBay Product ID (ePID)71989631

Product Key Features

Number of Pages400 Pages

LanguageEnglish

Publication NamePrinciples of Synthetic Intelligence : Psi: an Architecture of Motivated Cognition

Publication Year2009

SubjectIntelligence (Ai) & Semantics, Cognitive Psychology & Cognition

TypeTextbook

AuthorJoscha Bach

Subject AreaComputers, Psychology

SeriesOxford Series on Cognitive Models and Architectures Ser.

FormatHardcover

Dimensions

Item Height1.2 in

Item Weight24.6 Oz

Item Length9.3 in

Item Width6.4 in

Additional Product Features

Intended AudienceScholarly & Professional

LCCN2008-043048

Reviews"The first significant contribution of Dr. Bach's book is his introduction of Dorner's complete Psi architecture to an English-language audience. This contribution in and of itself is worthy of praise. But the true contribution of this book is more significant yet. I truly believe that twoof the most critical and overlooked components of a rigorous program to deeply understand the human mind are to think about mind broadly (instead of focusing solely on, say, drives or emotions or personality differences) and to build computational models that require the psychological andphilosophical models to be made fully explicit and grounded. Dr. Bach's approach leverages both. The Psi architecture is as broad in scope as any I have seen and the MicroPsi implementation grounds it in a working computational system." --Scott Neal Reilly, Principal Scientist, Charles River Analytics, Inc., "Bach's Principles of Synthetic Intelligence provides a thoughtful and detailed account of Dietrich Dorner's Psi cognitive architecture, finally making it available in English, where it joins other broad, comprehensive cognitive architectures such as the classics Soar and ACT-R, and my own,newer, LIDA. It's a must read for anyone wishing to explore how minds work via a comprehensive conceptual and computational cognitive model." --Stan Franklin, W. Harry Feinstone Interdisciplinary Research Professor, University of Memphis, "The book represents an important contribution to the existing theoretical and research-oriented literature on cognitive and cognitive-affective architectures, and is also very relevant to applied RandD in agent and robot architectures. Its key contributions include an extensive, in-depthreview of key issues in the design of cognitive and cognitive-affective architectures, which highlights fundamental issues in cognitive science, cognitive modeling, and affective modeling, and a clear description of an important psychological theory cognition, motivation and emotion, Dorner's Psitheory, which is not as well known in the English-speaking research community as it ought to be." --Eva Hudlicka, Principal Scientist, Psychometrix Associates, Inc., "A thought-provoking description of a long-running project on mental architecture, perhaps the most important topic in cognitive science today." --Margaret A. Boden, Research Professor of Cognitive Science, University of Sussex, "In Principles of Synthetic Intelligence Joscha Bach offers a new cognitive architecture that covers perhaps the broadest spectrum of phenomena accounted for to date by such architectures. The most seminal and challenging endeavor certainly consists in treating questions of motivation,autonomous behavior, and even emotions. These are important issues that will become benchmarks for future developments in the field." --Josef Nerb, Professor of Psychology, University of Education, Freiburg, "...outstanding...Overall, Bach inspires the reader to embrace the possibilities of AI, and his account of PSI theory and hte MicroPSI architecture and framework provide us with an exciting and fruitful new perspective on cognitive science and the philosophy of the mind."-- PsycCRITIQUES, "...outstanding...Overall, Bach inspires the reader to embrace the possibilities of AI, and his account of PSI theory and hte MicroPSI architecture and framework provide us with an exciting and fruitful new perspective on cognitive science and the philosophy of the mind."--PsycCRITIQUES

Dewey Edition22

IllustratedYes

Dewey Decimal153

Table Of Content1. Machines to explain the mind2. Dorner's "blueprint for a mind"3. Representation of and for mental processes4. Behavior control and action selection5. Language and future avenues6. Dorner's PSI agent implementation7. From PSI to MicroPSI: Reprsentations in the PSI Model8. The MicroPSI architecture9. The MicroPSI framework10. Summary: The PSI theory as a model of cognitionReferencesIndex

SynopsisAlthough computational models of cognition have become very popular, these models are relatively limited in their coverage of cognition-- they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. The first architecture to cover cognition more broadly is Psi theory, developed by Dietrich Dorner. By integrating motivation and emotion with perception and reasoning, and including grounded neuro-symbolic representations, Psi contributes significantly to an integrated understanding of the mind. It provides a conceptual framework that highlights the relationships between perception and memory, language and mental representation, reasoning and motivation, emotion and cognition, autonomy and social behavior. It is, however, unfortunate that Psi's origin in psychology, its methodology, and its lack of documentation have limited its impact. The proposed book adapts Psi theory to cognitive science and artificial intelligence, by elucidating both its theoretical and technical frameworks, and clarifying its contribution to how we have come to understand cognition., Although computational models of cognition have become very popular, these models are relatively limited in their coverage of cognition - they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. The first architecture to cover cognition more broadly is Psi theory, developed by Dietrich Dorner. By integrating motivation and emotion with perception and reasoning, and including grounded neuro-symbolic representations, Psi contributes significantly to an integrated understanding of the mind. It provides a conceptual framework that highlights the relationships between perception and memory, language and mental representation, reasoning and motivation, emotion and cognition, autonomy and social behavior. It is, however, unfortunate that Psi's origin in psychology, its methodology, and its lack of documentation have limited its impact. The proposed book adapts Psi theory to cognitive science and artificial intelligence, by elucidating both its theoretical and technical frameworks, and clarifying its contribution to how we have come to understand cognition., From the Foreword: "In this book Joscha Bach introduces Dietrich D rner's PSI architecture and Joscha's implementation of the MicroPSI architecture. These architectures and their implementation have several lessons for other architectures and models. Most notably, the PSI architecture includes drives and thus directly addresses questions of emotional behavior. An architecture including drives helps clarify how emotions could arise. It also changes the way that the architecture works on a fundamental level, providing an architecture more suited for behaving autonomously in a simulated world. PSI includes three types of drives, physiological (e.g., hunger), social (i.e., affiliation needs), and cognitive (i.e., reduction of uncertainty and expression of competency). These drives routinely influence goal formation and knowledge selection and application. The resulting architecture generates new kinds of behaviors, including context dependent memories, socially motivated behavior, and internally motivated task switching. This architecture illustrates how emotions and physical drives can be included in an embodied cognitive architecture. The PSI architecture, while including perceptual, motor, learning, and cognitive processing components, also includes several novel knowledge representations: temporal structures, spatial memories, and several new information processing mechanisms and behaviors, including progress through types of knowledge sources when problem solving (the Rasmussen ladder), and knowledge-based hierarchical active vision. These mechanisms and representations suggest ways for making other architectures more realistic, more accurate, and easier to use. The architecture is demonstrated in the Island simulated environment. While it may look like a simple game, it was carefully designed to allow multiple tasks to be pursued and provides ways to satisfy the multiple drives. It would be useful in its own right for developing other architectures interested in multi-tasking, long-term learning, social interaction, embodied architectures, and related aspects of behavior that arise in a complex but tractable real-time environment. The resulting models are not presented as validated cognitive models, but as theoretical explorations in the space of architectures for generating behavior. The sweep of the architecture can thus be larger-it presents a new cognitive architecture attempting to provide a unified theory of cognition. It attempts to cover perhaps the largest number of phenomena to date. This is not a typical cognitive modeling work, but one that I believe that we can learn much from." --Frank E. Ritter, Series Editor Although computational models of cognition have become very popular, these models are relatively limited in their coverage of cognition-- they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. The first architecture to cover cognition more broadly is PSI theory, developed by Dietrich Dorner. By integrating motivation and emotion with perception and reasoning, and including grounded neuro-symbolic representations, PSI contributes significantly to an integrated understanding of the mind. It provides a conceptual framework that highlights the relationships between perception and memory, language and mental representation, reasoning and motivation, emotion and cognition, autonomy and social behavior. It is, however, unfortunate that PSI's origin in psychology, its methodology, and its lack of documentation have limited its impact. The proposed book adapts Psi theory to cognitive science and artificial intelligence, by elucidating both its theoretical and technical frameworks, and clarifying its contribution to how we have come to understand cognition., From the Foreword: "In this book Joscha Bach introduces Dietrich Dörner's PSI architecture and Joscha's implementation of the MicroPSI architecture. These architectures and their implementation have several lessons for other architectures and models. Most notably, the PSI architecture includes drives and thus directly addresses questions of emotional behavior. An architecture including drives helps clarify how emotions could arise. It also changes the way that the architecture works on a fundamental level, providing an architecture more suited for behaving autonomously in a simulated world. PSI includes three types of drives, physiological (e.g., hunger), social (i.e., affiliation needs), and cognitive (i.e., reduction of uncertainty and expression of competency). These drives routinely influence goal formation and knowledge selection and application. The resulting architecture generates new kinds of behaviors, including context dependent memories, socially motivated behavior, and internally motivated task switching. This architecture illustrates how emotions and physical drives can be included in an embodied cognitive architecture. The PSI architecture, while including perceptual, motor, learning, and cognitive processing components, also includes several novel knowledge representations: temporal structures, spatial memories, and several new information processing mechanisms and behaviors, including progress through types of knowledge sources when problem solving (the Rasmussen ladder), and knowledge-based hierarchical active vision. These mechanisms and representations suggest ways for making other architectures more realistic, more accurate, and easier to use. The architecture is demonstrated in the Island simulated environment. While it may look like a simple game, it was carefully designed to allow multiple tasks to be pursued and provides ways to satisfy the multiple drives. It would be useful in its own right for developing other architectures interested in multi-tasking, long-term learning, social interaction, embodied architectures, and related aspects of behavior that arise in a complex but tractable real-time environment. The resulting models are not presented as validated cognitive models, but as theoretical explorations in the space of architectures for generating behavior. The sweep of the architecture can thus be larger-it presents a new cognitive architecture attempting to provide a unified theory of cognition. It attempts to cover perhaps the largest number of phenomena to date. This is not a typical cognitive modeling work, but one that I believe that we can learn much from." --Frank E. Ritter, Series Editor Although computational models of cognition have become very popular, these models are relatively limited in their coverage of cognition-- they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. The first architecture to cover cognition more broadly is PSI theory, developed by Dietrich Dorner. By integrating motivation and emotion with perception and reasoning, and including grounded neuro-symbolic representations, PSI contributes significantly to an integrated understanding of the mind. It provides a conceptual framework that highlights the relationships between perception and memory, language and mental representation, reasoning and motivation, emotion and cognition, autonomy and social behavior. It is, however, unfortunate that PSI's origin in psychology, its methodology, and its lack of documentation have limited its impact. The proposed book adapts Psi theory to cognitive science and artificial intelligence, by elucidating both its theoretical and technical frameworks, and clarifying its contribution to how we have come to understand cognition.

LC Classification NumberBF311.B23 2009