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16 results on '"Wang, Yingxu"'

2. A Knowledge Representation Tool for Autonomous Machine Learning Based on Concept Algebra

Author

Tian, Yousheng, Wang, Yingxu, Hu, Kai, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, and Chan, Keith C. C., editor

Published
2009
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3. Formal Description of the Cognitive Process of Memorization

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, and Chan, Keith C. C., editor

Published
2009
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4. Toward a Formal Knowledge System Theory and Its Cognitive Informatics Foundations

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, and Chan, Keith C. C., editor

Published
2009
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5. On Contemporary Denotational Mathematics for Computational Intelligence

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, Yao, Yiyu, editor, and Wang, Guoyin, editor

Published
2008
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6. On Mathematical Laws of Software

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, Yao, Yiyu, editor, and Wang, Guoyin, editor

Published
2008
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7. Perspectives on Denotational Mathematics: New Means of Thought

Author

Wang, Yingxu, Yao, Yiyu, Wang, Guoyin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Wang, Yingxu, editor, Yao, Yiyu, editor, and Wang, Guoyin, editor

Published
2008
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8. Cognitive Informatics and Denotational Mathematical Means for Brain Informatics

Author

Wang, Yingxu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Yao, Yiyu, editor, Sun, Ron, editor, Poggio, Tomaso, editor, Liu, Jiming, editor, Zhong, Ning, editor, and Huang, Jimmy, editor

Published
2010
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9. Abstract intelligence and cognitive robots

Author

Wang Yingxu

Subjects
cognitive informatics, cognitive computing, abstract intelligence, cognitive robots, computational intelligence, denotational mathematics, cognitive models, cognitive behaviors, behavioral modeling, Technology
Abstract

Abstract intelligence is the human enquiry of both natural and artificial intelligence at the neural, cognitive, functional, and logical levels reductively from the bottom up. According to the abstract intelligence theory, a cognitive robot is an autonomous robot that is capable of thought, perception, and learning based on the three-level computational intelligence known as the imperative, autonomic, and cognitive intelligence. This paper presents the theoretical foundations of cognitive robots based on the latest advances in abstract intelligence, cognitive informatics, and denotational mathematics. A formal model of intelligence known as the Generic Abstract Intelligence Mode (GAIM) is developed, which provides a foundation to explain the mechanisms of advanced natural intelligence such as thinking, learning, and inference. A set of denotational mathematics is introduced for rigorously modeling and manipulating the behaviors of cognitive robots. A case study on applications of a denotational mathematics, visual semantic algebra (VSA), is presented in architectural and behavioral modeling of cognitive robots based on the theory of abstract intelligence.

Published
2010
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10. Software and Intelligent Sciences : New Transdisciplinary Findings

Author

Wang, Yingxu and Wang, Yingxu

Subjects
Computer software, Computational intelligence
Abstract

'This book discusses the transdisciplinary field known as software and intelligence sciences covering an array of developments in computer science, theoretical software engineering, cognitive science, cognitive informatics, and intelligence science'--

Published
2012

11. On the Cognitive and Theoretical Foundations of Big Data Science and Engineering.

Author

Wang, Yingxu

Subjects
*BIG data, *COGNITIVE analysis, *ENGINEERING, *DATA, *DATA mining
Abstract

Big data play an indispensable role not only in the cognitive mechanisms of human sensation, quantification, qualification, estimation, memory, and reasoning, but also in a wide range of engineering applications. A basic study on the theoretical foundations of big data science is presented with a coherent set of general principles and analytic methodologies for big data systems. Cognitive foundations of big data are explored in order to formally explain the origination and nature of big data. A set of mathematical models of big data are created that rigorously elicit the general essences and patterns of big data across pervasive domains in sciences, engineering, and societies. A significant finding towards big data science is that big data systems in nature are a recursive -dimensional-typed hyperstructure (RNTHS) rather than pure numbers. The fundamental topological property of big data reveals a set of denotational mathematical solutions for dealing with inherited complexities and unprecedented challenges in big data engineering. [ABSTRACT FROM AUTHOR]

Published
2017
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12. On the cognitive process of human problem solving

Author

Wang, Yingxu and Chiew, Vincent

Subjects
*COGNITION, *PROBLEM solving, *ABSTRACT thought, *DATABASE searching, *COGNITIVE learning, *DECISION making, *MATHEMATICAL models, *BRAIN function localization
Abstract

Abstract: One of the fundamental human cognitive processes is problem solving. As a higher-layer cognitive process, problem solving interacts with many other cognitive processes such as abstraction, searching, learning, decision making, inference, analysis, and synthesis on the basis of internal knowledge representation by the object–attribute-relation (OAR) model. Problem solving is a cognitive process of the brain that searches a solution for a given problem or finds a path to reach a given goal. When a problem object is identified, problem solving can be perceived as a search process in the memory space for finding a relationship between a set of solution goals and a set of alternative paths. This paper presents both a cognitive model and a mathematical model of the problem solving process. The cognitive structures of the brain and the mechanisms of internal knowledge representation behind the cognitive process of problem solving are explained. The cognitive process is formally described using real-time process algebra (RTPA) and concept algebra. This work is a part of the cognitive computing project that designed to reveal and simulate the fundamental mechanisms and processes of the brain according to Wang’s layered reference model of the brain (LRMB), which is expected to lead to the development of future generation methodologies for cognitive computing and novel cognitive computers that are capable of think, learn, and perceive. [Copyright &y& Elsevier]

Published
2010
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13. Barriers to Implementing Computational Intelligence-Based Agriculture System

Author

Shafik, Wasswa, Kacprzyk, Janusz, Series Editor, Dorigo, Marco, Editorial Board Member, Engelbrecht, Andries, Editorial Board Member, Kreinovich, Vladik, Editorial Board Member, Morabito, Francesco Carlo, Editorial Board Member, Slowinski, Roman, Editorial Board Member, Wang, Yingxu, Editorial Board Member, Jin, Yaochu, Editorial Board Member, Sumithra, M. G., editor, Sathyamoorthy, Malathy, editor, Manikandan, M., editor, Dhanaraj, Rajesh Kumar, editor, and Ouaissa, Mariya, editor

Published
2024
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14. Computational Intelligence and Internet of Things in the Agriculture Sector: An Introduction

Author

Ouaissa, Mariyam, Ouaissa, Mariya, Himer, Sarah El, Sathyamoorthy, Malathy, Rajasekar, Vani, Dhanaraj, Rajesh Kumar, Kacprzyk, Janusz, Series Editor, Dorigo, Marco, Editorial Board Member, Engelbrecht, Andries, Editorial Board Member, Kreinovich, Vladik, Editorial Board Member, Morabito, Francesco Carlo, Editorial Board Member, Slowinski, Roman, Editorial Board Member, Wang, Yingxu, Editorial Board Member, Jin, Yaochu, Editorial Board Member, Sumithra, M. G., editor, Sathyamoorthy, Malathy, editor, Manikandan, M., editor, Dhanaraj, Rajesh Kumar, editor, and Ouaissa, Mariya, editor

Published
2024
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15. On abstract intelligence and brain informatics: Mapping the cognitive functions onto the neural architectures.

Author

Wang, Yingxu

Abstract

A fundamental challenge for almost all scientific disciplines is to explain how natural intelligence is generated by physiological organs and what the logical model of the brain is beyond its neural architectures. According to cognitive informatics and abstract intelligence, the exploration of the brain is a complicated recursive problem where contemporary denotational mathematics is needed to efficiently deal with it. Cognitive psychology and medical science are used to explain that the brain works in a certain way based on empirical observations of corresponding activities in usually overlapped brain areas. However, the lack of precise models and rigorous causality in brain studies has dissatisfied the formal expectations of researchers in computational science and mathematics, because a computer, the logical counterpart of the brain, might not be explained in such a vigor and empirical approach without the support of a formal model and a rigorous means. [ABSTRACT FROM PUBLISHER]

Published
2012
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