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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…mehr
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.
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.
Inhaltsangabe
1 Introduction 1.1 Cyber-Physical Society 1.2 Data 1.2.1 General definition of data 1.2.2 Data for computing 1.2.3 The philosophy of between material and mind 1.2.4 Views on Big Data 1.2.5 Big networks of data and humans 1.2.6 The shift of science paradigm 1.2.7 The fourth industrial revolution 1.2.8 Observed system, data, information, knowledge, humans and machines 1.2.9 Problems 2 Discovering Implicit Semantic Link in Cyber-Physical Society 2.1 Semantic Link 2.2 A brief history of Semantic Link Network 2.3 Knowledge flowing through semantic links 2.4 Modeling with local views and global views 2.5 The Big Gap 2.6 The Levels of Representation 2.7 The semantic link networks that enable intelligence 3 Dimensions on Data 3.1 Different views of Dimension 3.2 Dimensions on Big Data 3.3 Multi-dimensional category space 3.4 Complex multi-dimensional space and the tasks of analysis 4 Multi-Dimensional Analytics 4.1 Data operation dimension 4.2 System behavior dimension 4.3 Value dimension 4.4 Time dimension 4.5 Human dimension 4.6 Strategic planning on multiple dimensions an example 5 Unconventional Mapping from Data Space into Knowledge Space 5.1 Mapping Representations into Wikipedia 5.2 Mapping data space into knowledge space with cognition 5.3 Mapping data into human-level concepts 5.4 Mapping from representation into knowledge through complex modeling 5.5 From correlation to knowledge 5.6 Human representation and machine representation 5.7 Knowledge flow through cognitive systems 6 Cyber-Physical-Social Infrastructure 6.1 The development of Cyber-Infrastructure 6.2 Big gaps between humans and machines 6.3 Incorporating cognitive architecture into cyber-infrastructure 7 Communities of Cognition and Practice 8 New Paradigm of Science 8.1 The evolving paradigm of science 8.2 Science process with data, concept, motivation, thinking, knowledge and interaction 9 The Nature of Big Data Computing 9.1 The computing nature 9.2 Problem-driven, data-driven, and data-based problem driven 9.3 Beyond Turing test 9.4 Analogical mapping 9.5 Toward an open interactive computing 10 Mapping through Social Space 11 The Emergence of Cyber-Physical-Social Intelligence 11.1 Fundamental problem 11.2 Methodology 11.3 Understanding: extensible mapping from reality into mental space 11.4 Cyber-Physical-Social-Mental Computing 11.5 Laws of the complex system 12 Conclusion 13 References
1Introduction1.1Cyber-Physical Society1.2Data1.2.1General definition of data1.2.2Data for computing1.2.3The philosophy of between material and mind1.2.4Views on Big Data1.2.5Big networks of data and humans1.2.6The shift of science paradigm1.2.7The fourth industrial revolution1.2.8Observed system, data, information, knowledge, humans and machines1.2.9Problems2Discovering Implicit Semantic Link in Cyber-Physical Society2.1Semantic Link2.2A brief history of Semantic Link Network2.3Knowledge flowing through semantic links2.4Modeling with local views and global views2.5The Big Gap2.6The Levels of Representation2.7The semantic link networks that enable intelligence3Dimensions 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 analysis4Multi-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 example5Unconventional 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 6Cyber-Physical-Social Infrastructure6.1 The development of Cyber-Infrastructure6.2 Big gaps between humans and machines 6.3 Incorporating cognitive architecture into cyber-infrastructure7Communities of Cognition and Practice8New Paradigm of Science8.1 The evolving paradigm of science8.2 Science process with data, concept, motivation, thinking, knowledge and interaction9The 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 computing10Mapping through Social Space11The 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 system12Conclusion13References
1 Introduction 1.1 Cyber-Physical Society 1.2 Data 1.2.1 General definition of data 1.2.2 Data for computing 1.2.3 The philosophy of between material and mind 1.2.4 Views on Big Data 1.2.5 Big networks of data and humans 1.2.6 The shift of science paradigm 1.2.7 The fourth industrial revolution 1.2.8 Observed system, data, information, knowledge, humans and machines 1.2.9 Problems 2 Discovering Implicit Semantic Link in Cyber-Physical Society 2.1 Semantic Link 2.2 A brief history of Semantic Link Network 2.3 Knowledge flowing through semantic links 2.4 Modeling with local views and global views 2.5 The Big Gap 2.6 The Levels of Representation 2.7 The semantic link networks that enable intelligence 3 Dimensions on Data 3.1 Different views of Dimension 3.2 Dimensions on Big Data 3.3 Multi-dimensional category space 3.4 Complex multi-dimensional space and the tasks of analysis 4 Multi-Dimensional Analytics 4.1 Data operation dimension 4.2 System behavior dimension 4.3 Value dimension 4.4 Time dimension 4.5 Human dimension 4.6 Strategic planning on multiple dimensions an example 5 Unconventional Mapping from Data Space into Knowledge Space 5.1 Mapping Representations into Wikipedia 5.2 Mapping data space into knowledge space with cognition 5.3 Mapping data into human-level concepts 5.4 Mapping from representation into knowledge through complex modeling 5.5 From correlation to knowledge 5.6 Human representation and machine representation 5.7 Knowledge flow through cognitive systems 6 Cyber-Physical-Social Infrastructure 6.1 The development of Cyber-Infrastructure 6.2 Big gaps between humans and machines 6.3 Incorporating cognitive architecture into cyber-infrastructure 7 Communities of Cognition and Practice 8 New Paradigm of Science 8.1 The evolving paradigm of science 8.2 Science process with data, concept, motivation, thinking, knowledge and interaction 9 The Nature of Big Data Computing 9.1 The computing nature 9.2 Problem-driven, data-driven, and data-based problem driven 9.3 Beyond Turing test 9.4 Analogical mapping 9.5 Toward an open interactive computing 10 Mapping through Social Space 11 The Emergence of Cyber-Physical-Social Intelligence 11.1 Fundamental problem 11.2 Methodology 11.3 Understanding: extensible mapping from reality into mental space 11.4 Cyber-Physical-Social-Mental Computing 11.5 Laws of the complex system 12 Conclusion 13 References
1Introduction1.1Cyber-Physical Society1.2Data1.2.1General definition of data1.2.2Data for computing1.2.3The philosophy of between material and mind1.2.4Views on Big Data1.2.5Big networks of data and humans1.2.6The shift of science paradigm1.2.7The fourth industrial revolution1.2.8Observed system, data, information, knowledge, humans and machines1.2.9Problems2Discovering Implicit Semantic Link in Cyber-Physical Society2.1Semantic Link2.2A brief history of Semantic Link Network2.3Knowledge flowing through semantic links2.4Modeling with local views and global views2.5The Big Gap2.6The Levels of Representation2.7The semantic link networks that enable intelligence3Dimensions 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 analysis4Multi-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 example5Unconventional 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 6Cyber-Physical-Social Infrastructure6.1 The development of Cyber-Infrastructure6.2 Big gaps between humans and machines 6.3 Incorporating cognitive architecture into cyber-infrastructure7Communities of Cognition and Practice8New Paradigm of Science8.1 The evolving paradigm of science8.2 Science process with data, concept, motivation, thinking, knowledge and interaction9The 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 computing10Mapping through Social Space11The 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 system12Conclusion13References
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