Rigid Flexibility
The Logic of Intelligence
Published on 23. August 2006
Book
Hardback
XVIII, 402 pages
978-1-4020-5044-2 (ISBN)
Description
This book is the most comprehensive description of the decades-long Non-Axiomatic Reasoning System (NARS) project, including its philosophical foundation, methodological consideration, conceptual design details, implications in the related fields, and its similarities and differences to many related works in cognitive science. While most current works in Artificial Intelligence (AI) focus on individual aspects of intelligence and cognition, NARS is designed and developed to attack the AI problem as a whole.
Reviews / Votes
From the reviews:
"Rigid Flexibility presents a new theory of cognition. As such it is devoted to the general research for Artificial Intelligence (AI), in contrast to a focus of other AI research that is focusing on solving specific reasoning problems such as planning or learning for example. . The review of the principles and assumptions underlying the various streams of AI research make this book very interesting to read and enable the reader to easily compare the presented theory with other existing approaches." (Jana Koehler, Zentralblatt MATH, Vol. 1122 (24), 2007)
More details
Series
Edition
2006 ed.
Language
English
Place of publication
Dordrecht
Netherlands
Target group
Professional and scholarly
Research
Product notice
sewn/stitched
Cloth over boards
Illustrations
XVIII, 402 p.
Dimensions
Height: 248 mm
Width: 169 mm
Thickness: 27 mm
Weight
822 gr
ISBN-13
978-1-4020-5044-2 (9781402050442)
DOI
10.1007/1-4020-5045-3
Schweitzer Classification
Other editions
Additional editions
Book
10/2011
Springer
€213.99
Shipment within 15-20 days
E-Book
09/2006
1st Edition
Springer
€213.99
Available for download
Content
Theoretical Foundation.- The Goal of Artificial Intelligence.- A New Approach Toward AI.- Non-Axiomatic Reasoning System.- The Core Logic.- First-Order Inference.- Higher-Order Inference.- Inference Control.- Comparison and Discussion.- Semantics.- Uncertainty.- Inference Rules.- NAL as a Logic.- Categorization and Learning.- Control and Computation.- Conclusions.- Current Results.- NARS in the Future.