Overview
- Details the pragmatic requirements for real-world General Intelligence
- Provides a philosophical basis for the proposed approach
- Provides mathematical detail for a reference architecture
- This book is open access, which means that you have free and unlimited access
Part of the book series: Studies in Computational Intelligence (SCI, volume 1049)
Buy print copy
Tax calculation will be finalised at checkout
About this book
• Details the pragmatic requirements for real-world General Intelligence.
• Describes how machine learning fails to meet these requirements.
• Provides a philosophical basis for the proposed approach.
• Provides mathematical detail for a reference architecture.
• Describes a research program intended to address issues of concern in contemporary AI.
The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts
This is an open access book.
Similar content being viewed by others
Keywords
Table of contents (11 chapters)
-
-
Requirements
-
Semantically Closed Learning
Authors and Affiliations
About the authors
Bibliographic Information
Book Title: The Road to General Intelligence
Authors: Jerry Swan, Eric Nivel, Neel Kant, Jules Hedges, Timothy Atkinson, Bas Steunebrink
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-031-08020-3
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2022
Hardcover ISBN: 978-3-031-08019-7Published: 23 June 2022
eBook ISBN: 978-3-031-08020-3Published: 22 June 2022
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIV, 136
Number of Illustrations: 8 b/w illustrations, 18 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Data Engineering