Cyber-Physical-Social Intelligence: On Human-Machine-Nature Symbiosis

by Hai Zhuge

Overview

This book explores next-generation artificial intelligence based on the symbiosis between humans, machines and nature, including the rules and emerging patterns of recognition, and the integration and optimization of various flows through cyberspace, physical space and social space. It unveils a reciprocal human-machine-nature symbiotic mechanism together with relevant rules on structuring and evolving reality, and also proposes a multi-dimensional space for modelling reality and managing the methodologies for exploring reality. As such it lays the foundation for the emerging research area cyber-physical-social intelligence.  Inspiring researchers and university students to explore the development of intelligence and scientific methodology, it is intended for researchers and broad readers with a basic understanding of computer science and the natural sciences.

Next-generation artificial intelligence will extend machine intelligence and human intelligence to cyber-physical-social intelligence rendered by various interactions in cyberspace, physical space and social space. With the transformational development of science and society, a multi-dimensional reality is emerging and evolving, leading to the generation and development of various spaces obeying different principles. A fundamental scientific challenge is uncovering the essential mechanisms and principles that structure and evolve the reality emerging and evolving along various dimensions. Meeting this challenge requires identifying the basic relations between humans, machines and nature in order to reveal the cyber-physical-social principles.

Product Details

ISBN-13:	9789811373114
Publisher:	Springer-Verlag New York, LLC
Publication date:	11/12/2020
Sold by:	Barnes & Noble
Format:	eBook
File size:	33 MB
Note:	This product may take a few minutes to download.

About the Author

Hai Zhuge is an ACM (Association of Computer Machinery) Distinguished Scientist and a Fellow of the British Computer Society. He has made a systematic contribution to semantics and knowledge modelling through fundamental research on the Semantic Link Network and the Resource Space Model based on multi-dimensional methodology. He is leading research on cyber-physical-social intelligence using methodological, theoretical and technical innovations. As an ACM Distinguished Speaker, he has delivered 20 keynotes at international conferences and invited lectures at universities in various countries. As a Professor, he is head of an international research network consisting of the Guangzhou University, the Key Laboratory of Intelligent Information Processing at the Institute of Computing Technology in Chinese Academy of Sciences, the University of Chinese Academy of Sciences, and the System Analytics Research Institute at Aston University. He was a Distinguished Visiting Fellow of the Royal Academy of Engineering. He is the author of four monographs: Cyber-Physical-Social Intelligence on Human-Machine-Nature Symbiosis (Springer, 2019), Multi-Dimensional Summarization in Cyber-Physical Society (Morgan Kaufmann, 20016), The Knowledge Grid: Toward Cyber-Physical Society (World Scientific, 2012), and The Web Resource Space Model (Springer, 2008). He is currently as an Associate Editor of IEEE Intelligent Systems.

Table of Contents

1 Introduction1.1 Cyber-Physical Society1.2 Data1.2.1 General definition of data1.2.2 Data for computing1.2.3 The philosophy of between material and mind1.2.4 Views on Big Data1.2.5 Big networks of data and humans1.2.6 The shift of science paradigm1.2.7 The fourth industrial revolution1.2.8 Observed system, data, information, knowledge, humans and machines1.2.9 Problems2 Discovering Implicit Semantic Link in Cyber-Physical Society2.1 Semantic Link2.2 A brief history of Semantic Link Network2.3 Knowledge flowing through semantic links2.4 Modeling with local views and global views2.5 The Big Gap2.6 The Levels of Representation2.7 The semantic link networks that enable intelligence3 Dimensions on Data3.1 Different views of Dimension3.2 Dimensions on Big Data3.3 Multi-dimensional category space3.4 Complex multi-dimensional space and the tasks of analysis4 Multi-Dimensional Analytics4.1 Data operation dimension4.2 System behavior dimension4.3 Value dimension4.4 Time dimension4.5 Human dimension4.6 Strategic planning on multiple dimensions  an example5 Unconventional Mapping from Data Space into Knowledge Space5.1 Mapping Representations into Wikipedia5.2 Mapping data space into knowledge space with cognition5.3 Mapping data into human-level concepts5.4 Mapping from representation into knowledge through complex modeling5.5 From correlation to knowledge5.6 Human representation and machine representation5.7 Knowledge flow through cognitive systems 6 Cyber-Physical-Social Infrastructure6.1 The development of Cyber-Infrastructure6.2 Big gaps between humans and machines       6.3 Incorporating cognitive architecture into cyber-infrastructure7 Communities of Cognition and Practice8 New Paradigm of Science8.1 The evolving paradigm of science8.2 Science process with data, concept, motivation, thinking, knowledge and interaction9 The Nature of Big Data Computing9.1 The computing nature       9.2 Problem-driven, data-driven, and data-based problem driven9.3 Beyond Turing test9.4 Analogical mapping       9.5 Toward an open interactive computing10 Mapping through Social Space11 The Emergence of Cyber-Physical-Social Intelligence11.1 Fundamental problem11.2 Methodology11.3 Understanding: extensible mapping from reality into mental space       11.4 Cyber-Physical-Social-Mental Computing11.5 Laws of the complex system12 Conclusion13 References