Engineering General Intelligence, Part 1 - A Path to Advanced AGI via Embodied Learning and Cognitive Synergy

The work outlines a novel conceptual and theoretical framework for understanding Artificial General Intelligence and based on this framework outlines a practical roadmap for the development of AGI with capability at the human level and ultimately beyond.

List of contents

A Brief Overview of Cog Prime.- Build Me Something I Haven't Seen: A Cog Prime Thought Experiment.- What is Human-Like General Intelligence? A Patternist Philosophy of Mind.- Brief Survey of Cognitive Architectures.- A Generic Architecture of Human-Like Cognition.- A Formal Model of Intelligent Agents.- Cognitive Synergy.- General Intelligence in the Everyday Human World.- A Mind-World Correspondence Principle.- Stages of Cognitive Development.- The Engineering and Development of Ethics.- Local, Global and Glocal Knowledge Representation.- Representing Implicit Knowledge via Hypergraphs.- Emergent Networks of Intelligence.- AGI Preschool.- A Preschool-Based Roadmap to Advanced AGI.- Advanced Self-Modification: A Possible Path to Superhuman AGI.

Summary

The work outlines a novel conceptual and theoretical framework for understanding Artificial General Intelligence and based on this framework outlines a practical roadmap for the development of AGI with capability at the human level and ultimately beyond.

Product details

• Authors: Nil Geisweiller, Be Goertzel, Ben Goertzel, Cassi Pennachin, Cassio Pennachin
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 28.08.2013
• EAN: 9789462390263
• ISBN: 978-94-62-39026-3
• No. of pages: 409
• Dimensions: 163 mm x 243 mm x 28 mm
• Weight: 784 g
• Illustrations: XXII, 409 p. 105 illus., 32 illus. in color.
• Series: Atlantis Thinking Machines; Atlantis Thinking Machines
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; B, Artificial Intelligence, Neuroscience, computer science, complexity, Neurosciences, Computational Intelligence, Mathematical modelling, Neural networks (Computer science), Cybernetics & systems theory, Applied Dynamical Systems, Computational complexity, Cybernetics and systems theory