Abstract Intelligence

2020 ◽  
pp. 52-69
Author(s):  
Yingxu Wang ◽  
Lotfi A. Zadeh ◽  
Bernard Widrow ◽  
Newton Howard ◽  
Françoise Beaufays ◽  
...  
Keyword(s):  
Neural Networks ◽  
Mathematical Models ◽  
Computational Intelligence ◽  
Cognitive Learning ◽  
Cognitive Systems ◽  
Stanford University ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Basic Studies ◽  
Cognitive Robots

Basic studies in denotational mathematics and mathematical engineering have led to the theory of abstract intelligence (aI), which is a set of mathematical models of natural and computational intelligence in cognitive informatics (CI) and cognitive computing (CC). Abstract intelligence triggers the recent breakthroughs in cognitive systems such as cognitive computers, cognitive robots, cognitive neural networks, and cognitive learning. This paper reports a set of position statements presented in the plenary panel (Part II) of IEEE ICCI*CC'16 on Cognitive Informatics and Cognitive Computing at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.

scholarly journals Abstract Intelligence

2017 ◽  
Vol 11 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Yingxu Wang ◽  
Lotfi A. Zadeh ◽  
Bernard Widrow ◽  
Newton Howard ◽  
Françoise Beaufays ◽  
...  
Keyword(s):  
Neural Networks ◽  
Mathematical Models ◽  
Computational Intelligence ◽  
Cognitive Learning ◽  
Cognitive Systems ◽  
Stanford University ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Basic Studies ◽  
Cognitive Robots

Basic studies in denotational mathematics and mathematical engineering have led to the theory of abstract intelligence (aI), which is a set of mathematical models of natural and computational intelligence in cognitive informatics (CI) and cognitive computing (CC). Abstract intelligence triggers the recent breakthroughs in cognitive systems such as cognitive computers, cognitive robots, cognitive neural networks, and cognitive learning. This paper reports a set of position statements presented in the plenary panel (Part II) of IEEE ICCI*CC'16 on Cognitive Informatics and Cognitive Computing at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.

scholarly journals Cognitive Informatics

2018 ◽  
Vol 12 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Yingxu Wang ◽  
Newton Howard ◽  
Janusz Kacprzyk ◽  
Ophir Frieder ◽  
Phillip Sheu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computational Intelligence ◽  
Cognitive Robotics ◽  
Cognitive Systems ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Oxford University ◽  
Basic Studies ◽  
Intelligence Theories ◽  
The Brain

Cognitive Informatics (CI) is a contemporary field of basic studies on the brain, computational intelligence theories and underpinning denotational mathematics. Its applications include cognitive systems, cognitive computing, cognitive machine learning and cognitive robotics. IEEE ICCI*CC'17 on Cognitive Informatics and Cognitive Computing was focused on the theme of neurocomputation, cognitive machine learning and brain-inspired systems. This paper reports the plenary panel (Part I) at IEEE ICCI*CC'17 held at Oxford University. The summary is contributed by invited keynote speakers and distinguished panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and cognitive computing.

Cognitive Intelligence

2016 ◽  
Vol 10 (4) ◽  
pp. 1-20 ◽  
Author(s):  
Yingxu Wang ◽  
Bernard Widrow ◽  
Lotfi A. Zadeh ◽  
Newton Howard ◽  
Sally Wood ◽  
...  
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Computational Intelligence ◽  
Cognitive Systems ◽  
Cognitive Computing ◽  
Cognitive Intelligence ◽  
Basic Studies ◽  
Deep Reasoning ◽  
Intelligence Theories ◽  
The Brain

The theme of IEEE ICCI*CC'16 on Cognitive Informatics (CI) and Cognitive Computing (CC) was on cognitive computers, big data cognition, and machine learning. CI and CC are a contemporary field not only for basic studies on the brain, computational intelligence theories, and denotational mathematics, but also for engineering applications in cognitive systems towards deep learning, deep thinking, and deep reasoning. This paper reports a set of position statements presented in the plenary panel (Part I) in IEEE ICCI*CC'16 at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.

Cognitive Intelligence

2020 ◽  
pp. 1500-1523
Author(s):  
Yingxu Wang ◽  
Bernard Carlos Widrow ◽  
Lotfi A. Zadeh ◽  
Newton Howard ◽  
Sally Wood ◽  
...  
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Computational Intelligence ◽  
Cognitive Systems ◽  
Cognitive Computing ◽  
Cognitive Intelligence ◽  
Basic Studies ◽  
Deep Reasoning ◽  
Intelligence Theories ◽  
The Brain

The theme of IEEE ICCI*CC'16 on Cognitive Informatics (CI) and Cognitive Computing (CC) was on cognitive computers, big data cognition, and machine learning. CI and CC are a contemporary field not only for basic studies on the brain, computational intelligence theories, and denotational mathematics, but also for engineering applications in cognitive systems towards deep learning, deep thinking, and deep reasoning. This paper reports a set of position statements presented in the plenary panel (Part I) in IEEE ICCI*CC'16 at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.

Perspectives on Cognitive Informatics and Cognitive Computing

2010 ◽  
Vol 4 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Yingxu Wang ◽  
George Baciu ◽  
Yiyu Yao ◽  
Witold Kinsner ◽  
Keith Chan ◽  
...  
Keyword(s):  
Computational Linguistics ◽  
Computational Intelligence ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Intelligent Computing ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain ◽  
Science Information ◽  
Intelligence Science

Cognitive informatics is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. Cognitive computing is an emerging paradigm of intelligent computing methodologies and systems based on cognitive informatics that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This article presents a set of collective perspectives on cognitive informatics and cognitive computing, as well as their applications in abstract intelligence, computational intelligence, computational linguistics, knowledge representation, symbiotic computing, granular computing, semantic computing, machine learning, and social computing.

Perspectives on Cognitive Informatics and Cognitive Computing

2012 ◽  
pp. 1-24
Author(s):  
Yingxu Wang ◽  
George Baciu ◽  
Yiyu Yao ◽  
Witold Kinsner ◽  
Keith Chan ◽  
...  
Keyword(s):  
Computational Linguistics ◽  
Computational Intelligence ◽  
Social Computing ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Intelligent Computing ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain ◽  
Science Information

Cognitive informatics is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. Cognitive computing is an emerging paradigm of intelligent computing methodologies and systems based on cognitive informatics that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This article presents a set of collective perspectives on cognitive informatics and cognitive computing, as well as their applications in abstract intelligence, computational intelligence, computational linguistics, knowledge representation, symbiotic computing, granular computing, semantic computing, machine learning, and social computing.

On Cognitive Computing

2012 ◽  
pp. 83-97
Author(s):  
Yingxu Wang
Keyword(s):  
Computational Intelligence ◽  
Autonomic Computing ◽  
Theoretical Framework ◽  
Autonomous Agent ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Intelligent Computing ◽  
Agent Systems ◽  
The Brain ◽  
Theoretical Foundations

Inspired by the latest development in cognitive informatics and contemporary denotational mathematics, cognitive computing is an emerging paradigm of intelligent computing methodologies and systems, which implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This article presents a survey on the theoretical framework and architectural techniques of cognitive computing beyond conventional imperative and autonomic computing technologies. Theoretical foundations of cognitive computing are elaborated from the aspects of cognitive informatics, neural informatics, and denotational mathematics. Conceptual models of cognitive computing are explored on the basis of the latest advances in abstract intelligence and computational intelligence. Applications of cognitive computing are described from the aspects of autonomous agent systems and cognitive search engines, which demonstrate how machine and computational intelligence may be generated and implemented by cognitive computing theories and technologies toward autonomous knowledge processing.

On Cognitive Models of Causal Inferences and Causation Networks

2011 ◽  
Vol 3 (1) ◽  
pp. 50-60 ◽  
Author(s):  
Yingxu Wang
Keyword(s):  
Problem Solving ◽  
Mathematical Models ◽  
Causal Inference ◽  
Computational Intelligence ◽  
Theoretical Foundation ◽  
Cognitive Models ◽  
Human Reasoning ◽  
Cognitive Computing ◽  
Causal Inferences ◽  
Human Thought

Human thought, perception, reasoning, and problem solving are highly dependent on causal inferences. This paper presents a set of cognitive models for causation analyses and causal inferences. The taxonomy and mathematical models of causations are created. The framework and properties of causal inferences are elaborated. Methodologies for uncertain causal inferences are discussed. The theoretical foundation of humor and jokes as false causality is revealed. The formalization of causal inference methodologies enables machines to mimic complex human reasoning mechanisms in cognitive informatics, cognitive computing, and computational intelligence.

The Cognitive Mechanisms and Formal Models of Consciousness

2012 ◽  
Vol 6 (2) ◽  
pp. 23-40 ◽  
Author(s):  
Yingxu Wang
Keyword(s):  
Computational Intelligence ◽  
Cognitive Process ◽  
Formal Model ◽  
Sense Of Self ◽  
Human Perception ◽  
Cognitive Computing ◽  
Cognitive Mechanisms ◽  
Cognitive Informatics ◽  
Internal States ◽  
Rigorous Mathematical Model

Consciousness is the sense of self and the sign of life in natural intelligence. One of the profound myths in cognitive informatics, psychology, brain science, and computational intelligence is how consciousness is generated by physiological organs and neural networks in the bran. This paper presents a formal model and a cognitive process of consciousness in order to explain how abstract consciousness is generated and what its cognitive mechanisms are. The hierarchical levels of consciousness are explored from the facets of neurology, physiology, and computational intelligence. A rigorous mathematical model of consciousness is created that elaborates the nature of consciousness. The cognitive process of consciousness is formally described using denotational mathematics. It is recognized that consciousness is a set of real-time mental information about bodily and emotional status of an individual stored in the cerebellums known as the Conscious Status Memory (CSM) and is processed/interpreted by the thalamus. The abstract intelligence model of consciousness can be applied in cognitive informatics, cognitive computing, and computational intelligence toward the mimicry and simulation of human perception and awareness of the internal states, external environment, and their interactions in reflexive, perceptive, cognitive, and instructive intelligence.

Towards the Synergy of Cognitive Informatics, Neural Informatics, Brain Informatics, and Cognitive Computing

2012 ◽  
pp. 1-19 ◽  
Author(s):  
Yingxu Wang
Keyword(s):  
Intelligent Systems ◽  
Reference Model ◽  
External Information ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Learning Machines ◽  
Cognitive Knowledge ◽  
The Mind ◽  
Cognitive Robots ◽  
The Brain

The contemporary wonder of sciences and engineering recently refocused on the starting point: how the brain processes internal and external information autonomously rather than imperatively as those of conventional computers? This paper explores the interplay and synergy of cognitive informatics, neural informatics, abstract intelligence, denotational mathematics, brain informatics, and computational intelligence. A key notion recognized in recent studies in cognitive informatics is that the root and profound objective in natural, abstract, and artificial intelligence, and in cognitive informatics and cognitive computing, is to seek suitable mathematical means for their special needs. A layered reference model of the brain and a set of cognitive processes of the mind are systematically developed towards the exploration of the theoretical framework of cognitive informatics. A wide range of applications of cognitive informatics and denotational mathematics are recognized in the development of highly intelligent systems such as cognitive computers, cognitive knowledge search engines, autonomous learning machines, and cognitive robots.

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