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Theoretical Foundations of Artificial General Intelligence

by Wang, Pei.
Authors: Goertzel, Ben.%editor. | SpringerLink (Online service) Series: Atlantis Thinking Machines, 1877-3273 ; . 4 Physical details: IX, 330 p. 37 illus., 4 illus. in color. online resource. ISBN: 9491216627 Subject(s): Computer science. | Artificial intelligence. | Computer simulation. | Consciousness. | Computer Science. | Artificial Intelligence (incl. Robotics). | Models and Principles. | Simulation and Modeling. | Cognitive Psychology.
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E-Book E-Book AUM Main Library 006.3 (Browse Shelf) Not for loan

Introduction -- Artificial Intelligence and Cognitive Modeling Have the Same Problem -- The Piaget-MacGuyver Room -- Beyond the Octopus: From General Intelligence toward a Human-like Mind -- One Decade of Universal Artificial Intelligence -- Deep Reinforcement Learning as Foundation for Artificial General Intelligence -- The LIDA Model as a Foundational Architecture for AGI -- The Architecture of Human-Like General Intelligence -- A New Constructivist AI -- Towards an Actual Gödel Machine Implementation -- Artificial General Intelligence Begins with Recognition -- Theory Blending as a Framework for Creativity in Systems for General Intelligence -- Modeling Emotion and Affect -- AGI and Machine Consciousness -- Human and Machine Consciousness as a Boundary Effect in the Concept -- Theories of Artificial Intelligence.

This book is a collection of writings by active researchers in the field of Artificial General Intelligence, on topics of central importance in the field. Each chapter focuses on one theoretical problem, proposes a novel solution, and is written in sufficiently non-technical language to be understandable by advanced undergraduates or scientists in allied fields. This book is the very first collection in the field of Artificial General Intelligence (AGI) focusing on theoretical, conceptual, and philosophical issues in the creation of thinking machines. All the authors are researchers actively developing AGI projects, thus distinguishing the book from much of the theoretical cognitive science and AI literature, which is generally quite divorced from practical AGI system building issues. And the discussions are presented in a way that makes the problems and proposed solutions understandable to a wide readership of non-specialists, providing a distinction from the journal and conference-proceedings literature. The book will benefit AGI researchers and students by giving them a solid orientation in the conceptual foundations of the field (which is not currently available anywhere); and it would benefit researchers in allied fields by giving them a high-level view of the current state of thinking in the AGI field. Furthermore, by addressing key topics in the field in a coherent way, the collection as a whole may play an important role in guiding future research in both theoretical and practical AGI, and in linking AGI research with work in allied disciplines

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