Authors:
No other book (or research paper) provides a detailed, carefully-argued roadmap for getting from the present state of AI technology to the creation of Artificial General Intelligence with capability at the human level and beyond
No other book (or research paper) bridges the gap between the abstract, mathematical theory of general intelligence and real-world general intelligence as demonstrated by humans and other practically achievable AGI systems
The book gives concrete guidance for the creation of virtual worlds and robotic environments suitable for the education and development of advanced Artificial General Intelligence systems
Includes supplementary material: sn.pub/extras
Part of the book series: Atlantis Thinking Machines (ATLANTISTM, volume 5)
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Table of contents (19 chapters)
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Front Matter
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Overview of the CogPrime Architecture
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Front Matter
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Artificial and Natural General Intelligence
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Front Matter
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Toward a General Theory of General Intelligence
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Front Matter
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Cognitive and Ethical Development
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Front Matter
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Networks for Explicit and Implicit Knowledge Representation
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Front Matter
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About this book
Authors and Affiliations
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G/F 51C Lung Mei Village, Tai Po, Hong Kong, China
Ben Goertzel
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Igenesis, Minas Gerais, Brazil
Cassio Pennachin
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Samokov, Bulgaria
Nil Geisweiller
Bibliographic Information
Book Title: Engineering General Intelligence, Part 1
Book Subtitle: A Path to Advanced AGI via Embodied Learning and Cognitive Synergy
Authors: Ben Goertzel, Cassio Pennachin, Nil Geisweiller
Series Title: Atlantis Thinking Machines
DOI: https://doi.org/10.2991/978-94-6239-027-0
Publisher: Atlantis Press Paris
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Atlantis Press and the authors 2014
Hardcover ISBN: 978-94-6239-026-3Published: 12 March 2014
eBook ISBN: 978-94-6239-027-0Published: 08 July 2014
Series ISSN: 1877-3273
Series E-ISSN: 1877-3281
Edition Number: 1
Number of Pages: XXII, 409
Number of Illustrations: 73 b/w illustrations, 32 illustrations in colour
Topics: Artificial Intelligence, Computational Intelligence, Complexity, Neurosciences, Mathematical Models of Cognitive Processes and Neural Networks