Semantic and Formal Representation of Cognitive Models for the Metacognitive Architecture CARINA

2021 ◽  
pp. 54-72
Author(s):  
Alba J. Jerónimo ◽  
María P. Barrera ◽  
Manuel F. Caro ◽  
Adán A. Gómez
Keyword(s):  
Knowledge Representation ◽  
Semantic Memory ◽  
Cognitive Model ◽  
Semantic Knowledge ◽  
Cognitive Models ◽  
Formal Representation ◽  
Object Properties ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain

A cognitive model is a computational model of internal information processing mechanisms of the brain for the purposes of comprehension and prediction. CARINA metacognitive architecture runs cognitive models. However, CARINA does not currently have mechanisms to store and learn from cognitive models executed in the past. Semantic knowledge representation is a field of study which concentrates on using formal symbols to a collection of propositions, objects, object properties, and relations among objects. In CARINA Beliefs are a form of represent the semantic knowledge. The aim of this chapter is to formally describe a CARINA-based cognitive model through of denotational mathematics and to represent these models using a technique of semantic knowledge representation called beliefs. All the knowledge received by CARINA is stored in the semantic memory in the form of beliefs. Thus, a cognitive model represented through beliefs will be ready to be stored in semantic memory of the metacognitive architecture CARINA. Finally, an illustrative example is presented.

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.

Perspectives on the Field of Cognitive Informatics and its Future Development

2012 ◽  
pp. 20-34
Author(s):  
Yingxu Wang ◽  
Bernard Carlos Widrow ◽  
Bo Zhang ◽  
Witold Kinsner ◽  
Kenji Sugawara ◽  
...  
Keyword(s):  
Information Processing ◽  
Computer Science ◽  
Future Development ◽  
External Information ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain ◽  
Science Information

The contemporary wonder of sciences and engineering has recently refocused on the beginning point of: how the brain processes internal and external information autonomously and cognitively rather than imperatively like conventional computers. Cognitive Informatics (CI) 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. This paper reports a set of eight position statements presented in the plenary panel of IEEE ICCI’10 on Cognitive Informatics and Its Future Development contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

A General Knowledge Representation Model for the Acquisition of Skills and Concepts

2012 ◽  
Vol 4 (4) ◽  
pp. 1-25
Author(s):  
Carlos Ramírez ◽  
Benjamín Valdés
Keyword(s):  
Knowledge Representation ◽  
Learning Environments ◽  
Cognitive Model ◽  
Semantic Knowledge ◽  
Context Information ◽  
General Knowledge ◽  
Constructivist Approach ◽  
Computational Implementation ◽  
Relevant Context ◽  
Role Based

A cognitive model for skills and concepts representation as well as a proposal for its computational implementation is presented. The model is intended to help bridge some of the natural problems that arise in current massive education models, through the adaptation and personalisation of learning environments. The model is capable of representing rich semantic knowledge, including both, skills and concepts, integrating them through a coherent network of role based associations. The associations build an ontology that integrates on itself different domain taxonomies to represent the knowledge acquired by a student keeping relevant context information. The model is based on a constructivist approach.

A General Knowledge Representation Model for the Acquisition of Skills and Concepts

2010 ◽  
Vol 2 (3) ◽  
pp. 1-20 ◽  
Author(s):  
Carlos Ramirez ◽  
Benjamin Valdes
Keyword(s):  
Knowledge Representation ◽  
Learning Environments ◽  
Cognitive Model ◽  
Semantic Knowledge ◽  
Context Information ◽  
General Knowledge ◽  
Constructivist Approach ◽  
Computational Implementation ◽  
Relevant Context ◽  
Role Based

A cognitive model for skills and concepts representation as well as a proposal for its computational implementation is presented in this paper. The model is intended to help bridge some of the natural problems that arise in current massive education models through the adaptation and personalization of learning environments. The model is capable of representing rich semantic knowledge, including both skills and concepts, while integrating them through a coherent network of role based associations. The associations build an ontology that integrates on itself different domain taxonomies to represent the knowledge acquired by a student keeping relevant context information. The model is based on a constructivist approach.

Formal RTPA Models for a Set of Meta-Cognitive Processes of the Brain

2011 ◽  
pp. 308-324
Author(s):  
Yingxu Wang
Keyword(s):  
Mathematical Model ◽  
Knowledge Representation ◽  
Cognitive Processes ◽  
Process Model ◽  
Object Identification ◽  
Time Process ◽  
Metacognitive Processes ◽  
Internal Information ◽  
The Brain ◽  
Object Attribute

The cognitive processes modeled at the metacognitive level of the layered reference mode of the brain (LRMB) encompass those of object identification, abstraction, concept establishment, search, categorization, comparison, memorization, qualification, quantification, and selection. It is recognized that all higher layer cognitive processes of the brain rely on the metacognitive processes. Each of this set of fundamental cognitive processes is formally described by a mathematical model and a process model. Real-time process algebra (RTPA) is adopted as a denotational mathematical means for rigorous modeling and describing the metacognitive processes. All cognitive models and processes are explained on the basis of the object-attribute-relation (OAR) model for internal information and knowledge representation and manipulation.

Cognitive Informatics and Cognitive Computing in Year 10 and Beyond

2011 ◽  
Vol 5 (4) ◽  
pp. 1-21 ◽  
Author(s):  
Yingxu Wang ◽  
Robert C. Berwick ◽  
Simon Haykin ◽  
Witold Pedrycz ◽  
Witold Kinsner ◽  
...  
Keyword(s):  
Information Processing ◽  
Computer Science ◽  
Cognitive Science ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain ◽  
Science Information ◽  
Intelligence Science

Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. The latest advances in CI leads to the establishment of cognitive computing theories and methodologies, as well as the development of Cognitive Computers (CogC) that perceive, infer, and learn. This paper reports a set of nine position statements presented in the plenary panel of IEEE ICCI*CC’11 on Cognitive Informatics in Year 10 and Beyond contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

A Computational Cognitive Model of the Brain

2011 ◽  
pp. 1-17
Author(s):  
Zhiwei Shi ◽  
Hong Hu ◽  
Zhongzhi Shi
Keyword(s):  
Knowledge Representation ◽  
Human Brain ◽  
Experimental Evidence ◽  
Graphical Model ◽  
Cognitive Model ◽  
Similarity Measurement ◽  
Top Down ◽  
Knowledge Accumulation ◽  
Computational Explanation ◽  
The Brain

Recent fruitful progresses on brain science have largely broadened our understanding of the cerebrum. These great works led us to propose a computational cognitive model based on a graphical model that we carried out before. The model possesses many attractive properties, including distinctive knowledge representation, the capability of knowledge accumulation, active (top-down) attention, subjective similarity measurement, and attention-guided disambiguation. It also has “consciousness” and can even “think” and “make inference.” To some extent, it works just like the human brain does. The experimental evidence demonstrates that it can give reasonable computational explanation on the human phenomenon of forgetting. Although there are still some undetermined details and neurobiological mechanisms deserving consideration, our work presents a meaningful attempt to give further insights into the brain’s functions.

Cognitive Informatics

2011 ◽  
pp. 104-111 ◽  
Author(s):  
Yingxu Wang
Keyword(s):  
Information Processing ◽  
Computer Science ◽  
Knowledge Engineering ◽  
Systems Science ◽  
Science And Engineering ◽  
Cognitive Informatics ◽  
Knowledge Based ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain

Cognitive informatics (CI) is an emerging discipline that studies the natural intelligence and internal information processing mechanisms of the brain, as well as the processes involved in perception and cognition. CI provides a coherent set of fundamental theories and contemporary mathematics that form the foundation for most information- and knowledge-based science and engineering disciplines, such as computer science, cognitive science, neuropsychology, systems science, cybernetics, software engineering, and knowledge engineering.

Perspectives on eBrain and Cognitive Computing

2012 ◽  
Vol 6 (4) ◽  
pp. 1-21 ◽  
Author(s):  
Yingxu Wang ◽  
James A. Anderson ◽  
George Baciu ◽  
Gerhard Budin ◽  
D. Frank Hsu ◽  
...  
Keyword(s):  
Cognitive Linguistics ◽  
Information Science ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Internal Information ◽  
Processing Mechanisms ◽  
Intelligence Theories ◽  
The Brain ◽  
Science Information ◽  
Intelligence Science

Cognitive Informatics (CI) is a discipline spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, and cognitive linguistics. CI aims to investigate the internal information processing mechanisms and processes of the brain, the underlying abstract intelligence theories and denotational mathematics, and their engineering applications in cognitive computing and computational intelligence. This paper reports a set of nine position statements presented in the plenary panel of IEEE ICCI*CC’12 on eBrain and Cognitive Computers contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

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