Theoretical Foundations of Artificial General Intelligence

1. Front Matter

   Pages i-ix

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2. Introduction: What Is the Matter Here?

   • Pei Wang, Ben Goertzel

   Pages 1-9

3. Artificial Intelligence and Cognitive Modeling Have the Same Problem

   • Nicholas L. Cassimatis

   Pages 11-24

4. Psychometric Artificial General Intelligence: The Piaget-MacGuyver Room

   • Selmer Bringsjord, John Licato

   Pages 25-48

5. Beyond the Octopus: From General Intelligence Toward a Human-Like Mind

   • Sam S. Adams, Steve Burbeck

   Pages 49-65

6. One Decade of Universal Artificial Intelligence

   • Marcus Hutter

   Pages 67-88

7. Deep Reinforcement Learning as Foundation for Artificial General Intelligence

   • Itamar Arel

   Pages 89-102

8. The LIDA Model as a Foundational Architecture for AGI

   • Usef Faghihi, Stan Franklin

   Pages 103-121

9. The Architecture of Human-Like General Intelligence

   • Ben Goertzel, Matt Iklé, Jared Wigmore

   Pages 123-144

10. A New Constructivist AI: From Manual Methods to Self-Constructive Systems

    • Kristinn R. Thórisson

    Pages 145-171

11. Towards an Actual Gödel Machine Implementation: a Lesson in Self-Reflective Systems

    • Bas R. Steunebrink, Jürgen Schmidhuber

    Pages 173-195

12. Artificial General Intelligence Begins With Recognition: Evaluating the Flexibility of Recognition

    • Tsvi Achler

    Pages 197-217

13. Theory Blending as a Framework for Creativity in Systems for General Intelligence

    • Maricarmen Martinez, Tarek R. Besold, Ahmed Abdel-Fattah, Helmar Gust, Martin Schmidt, Ulf Krumnack et al.

    Pages 219-239

14. Modeling Motivation and the Emergence of Affect in a Cognitive Agent

    • Joscha Bach

    Pages 241-262

15. AGI and Machine Consciousness

    • Antonio Chella, Riccardo Manzotti

    Pages 263-282

16. Human and Machine Consciousness as a Boundary Effect in the Concept Analysis Mechanism

    • Richard Loosemore

    Pages 283-304

17. Theories of Artificial Intelligence—Meta-Theoretical considerations

    • Pei Wang

    Pages 305-323

18. Back Matter

    Pages 325-330

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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

• artificial intelligence
• brain theory
• cognitive science
• neuroscience
• thinking machines

• , Department of Computer, Temple University, Philadelphia, USA

  Pei Wang

• Biomind LLC, Novamente LLC/, Rockville, USA

  Ben Goertzel

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