This book provides the blueprint of a thinking machine.

While most of the current works in Artificial Intelligence (AI) focus on individual aspects of intelligence and cognition, the project described in this book, Non-Axiomatic Reasoning System (NARS), is designed and developed to attack the AI problem as a whole.

This project is based on the belief that what we call "intelligence" can be understood and reproduced as "the capability of a system to adapt to its environment while working with insufficient knowledge and resources". According to this idea, a novel reasoning system is designed, which challenges all the dominating theories in how such a system should be built. The system carries out reasoning, learning, categorizing, planning, decision making, etc., as different facets of the same underlying process. This theory also provides unified solutions to many problems in AI, logic, psychology, and philosophy.

This book is the most comprehensive description of this decades-long project, including its philosophical foundation, methodological consideration, conceptual design details, its implications in the related fields, as well as its similarities and differences to many related works in cognitive sciences.

One of a small number of books that try to give a constructive explanation of intelligence/cognition/thinking as a whole A novel and original approach that challenges all dominating theories Theoretical discussions combined with design details Unified solutions to many traditional problems in several fields (artificial intelligence, logic, psychology, philosophy, linguistics, )

Autorentext

Jinhu Lü is a Full Professor and the Dean of the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China, and a Professor at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences. He received his Ph.D. in Applied Mathematics from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, in 2002. He was a Professor at RMIT University, Melbourne, Australia, and a Visiting Fellow at Princeton University, USA. He is a Chief Scientist in the National Key Research and Development Program of China and a Leading Scientist in the Innovative Research Groups of the National Natural Science Foundation of China. His current research interests include complex networks, cooperation control, and the industrial Internet. He is the author of four research monographs and more than 200 SCI journal papers. Dr. Lü was a recipient of the prestigious Ho Leung Ho Lee Foundation Award in 2015; the Chinese Government's State Natural Science Award in 2008, 2012, and 2016; the Australian Research Council Future Fellowships Award in 2009; the National Natural Science Fund for Distinguished Young Scholars Award; and Highly Cited Researcher Awards in engineering from 2014 to 2019. He is/was an Editor for 15 SCI journals, including the Co-Editor-in-Chief of IEEE TII, and served on the Fellows Evaluating Committee of the IEEE CASS, the IEEE CIS, and the IEEE IES. He was the general Co-Chair of IECON 2017. He is a Fellow of IEEE and CAA. Pei Wang is an Associate Professor at the School of Mathematics and Statistics, Henan University, Kaifeng, China. He received his M.Sc. and Ph.D. in Computational Mathematics from the School of Mathematics and Statistics, Wuhan University, China, in 2009 and 2012, respectively. He was a Visiting Research Fellow at the School of Electrical and Computer Engineering, RMIT University, Melbourne, Australia. His research interests include biostatistics, systems biology, andcomplex networks. He is the author of more than 30 SCI journal papers, and serves as a reviewer for the American Mathematical Reviews. He is a member of the Technical Committee on Complex Systems and Complex Networks, China Society for Industrial and Applied Mathematics.

Klappentext

This book provides the blueprint of a thinking machine.

While most of the current works in Artificial Intelligence (AI) focus on individual aspects of intelligence and cognition, the project described in this book, Non-Axiomatic Reasoning System (NARS), is designed and developed to attack the AI problem as a whole.

This project is based on the belief that what we call "intelligence" can be understood and reproduced as "the capability of a system to adapt to its environment while working with insufficient knowledge and resources". According to this idea, a novel reasoning system is designed, which challenges all the dominating theories in how such a system should be built. The system carries out reasoning, learning, categorizing, planning, decision making, etc., as different facets of the same underlying process. This theory also provides unified solutions to many problems in AI, logic, psychology, and philosophy.

This book is the most comprehensive description of this decades-long project, including its philosophical foundation, methodological consideration, conceptual design details, its implications in the related fields, as well as its similarities and differences to many related works in cognitive sciences.

Zusammenfassung

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.

Inhalt
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.