The Cognitive Process of Comprehension

2010 ◽  
Vol 4 (3) ◽  
pp. 44-58 ◽  
Author(s):  
Yingxu Wang ◽  
Davrondzhon Gafurov
Keyword(s):  
Cognitive Processes ◽  
Intelligent Systems ◽  
Cognitive Process ◽  
Process Algebra ◽  
Formal Model ◽  
Reference Model ◽  
Process Models ◽  
Abstract Thought ◽  
Comprehension Process ◽  
The Brain

Comprehension is an ability to understand the meaning of a concept or an action. Comprehension is an important intelligent power of abstract thought and reasoning of humans or intelligent systems. It is highly curious to explore the internal process of comprehension in the brain and to explain its basic mechanisms in cognitive informatics and computational intelligence. This paper presents a formal model of the cognitive process of comprehension. The mechanism and process of comprehension are systematically explained with its conceptual, mathematical, and process models based on the Layered Reference Model of the Brain (LRMB) and the Object-Attribute-Relation (OAR) model for internal knowledge representation. Contemporary denotational mathematics such as concept algebra and Real-Time Process Algebra (RTPA) are adopted in order to formally describe the comprehension process and its interaction with other cognitive processes of the brain.

The Cognitive Process of Comprehension

2012 ◽  
pp. 25-37 ◽  
Author(s):  
Yingxu Wang ◽  
Davrondzhon Gafurov
Keyword(s):  
Computational Intelligence ◽  
Intelligent Systems ◽  
Cognitive Process ◽  
Formal Model ◽  
Reference Model ◽  
Process Models ◽  
Abstract Thought ◽  
Comprehension Process ◽  
The Brain ◽  
Object Attribute

Comprehension is an ability to understand the meaning of a concept or an action. Comprehension is an important intelligent power of abstract thought and reasoning of humans or intelligent systems. It is highly curious to explore the internal process of comprehension in the brain and to explain its basic mechanisms in cognitive informatics and computational intelligence. This paper presents a formal model of the cognitive process of comprehension. The mechanism and process of comprehension are systematically explained with its conceptual, mathematical, and process models based on the Layered Reference Model of the Brain (LRMB) and the Object-Attribute-Relation (OAR) model for internal knowledge representation. Contemporary denotational mathematics such as concept algebra and Real-Time Process Algebra (RTPA) are adopted in order to formally describe the comprehension process and its interaction with other cognitive processes of the brain.

The Cognitive Processes of Formal Inferences

2011 ◽  
pp. 92-105
Author(s):  
Yingxu Wang
Keyword(s):  
Mathematical Models ◽  
Causal Inference ◽  
Real Time ◽  
Cognitive Processes ◽  
Cognitive Process ◽  
Process Algebra ◽  
Applied Research ◽  
Theoretical Research ◽  
Time Process ◽  
The Brain

Theoretical research is predominately an inductive process, while applied research is mainly a deductive process. Both inference processes are based on the cognitive process and means of abstraction. This chapter describes the cognitive processes of formal inferences such as deduction, induction, abduction, and analogy. Conventional propositional arguments adopt static causal inference. This chapter introduces more rigorous and dynamic inference methodologies, which are modeled and described as a set of cognitive processes encompassing a series of basic inference steps. A set of mathematical models of formal inference methodologies is developed. Formal descriptions of the 4 forms of cognitive processes of inferences are presented using Real-Time Process Algebra (RTPA). The cognitive processes and mental mechanisms of inferences are systematically explored and rigorously modeled. Applications of abstraction and formal inferences in both the revilement of the fundamental mechanisms of the brain and the investigation of next generation cognitive computers are explored.

scholarly journals Should I stay or should I go? Evidence accumulation drives decision making in human drivers

2020 ◽  
Author(s):  
Arkady Zgonnikov ◽  
David Abbink ◽  
Gustav Markkula
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Cognitive Process ◽  
Response Times ◽  
Process Models ◽  
Cognitive Mechanisms ◽  
Naturalistic Decision Making ◽  
Dynamic Constraints ◽  
Evidence Accumulation ◽  
Out Of Sample

Laboratory studies of abstract, highly controlled tasks point towards noisy evidence accumulation as a key mechanism governing decision making. Yet it is unclear whether the cognitive processes implicated in simple, isolated decisions in the lab are as paramount to decisions that are ingrained in more complex behaviors, such as driving. Here we aim to address the gap between modern cognitive models of decision making and studies of naturalistic decision making in drivers, which so far have provided only limited insight into the underlying cognitive processes. We investigate drivers' decision making during unprotected left turns, and model the cognitive process driving these decisions. Our model builds on the classical drift-diffusion model, and emphasizes, first, the drift rate linked to the relevant perceptual quantities dynamically sampled from the environment, and, second, collapsing decision boundaries reflecting the dynamic constraints imposed on the decision maker’s response by the environment. We show that the model explains the observed decision outcomes and response times, as well as substantial individual differences in those. Through cross-validation, we demonstrate that the model not only explains the data, but also generalizes to out-of-sample conditions, effectively providing a way to predict human drivers’ behavior in real time. Our results reveal the cognitive mechanisms of gap acceptance decisions in human drivers, and exemplify how simple cognitive process models can help us to understand human behavior in complex real-world tasks.

On Cognitive Foundations of Creativity and the Cognitive Process of Creation

2009 ◽  
Vol 3 (4) ◽  
pp. 1-18 ◽  
Author(s):  
Yingxu Wang
Keyword(s):  
Problem Solving ◽  
Cognitive Process ◽  
Reference Model ◽  
Human Beings ◽  
Inference Problem ◽  
Tree Structures ◽  
Structures And Properties ◽  
Cognitive Foundations ◽  
The Relationship ◽  
The Brain

Creativity is a gifted ability of human beings in thinking, inference, problem solving, and product development. A creation is a new and unusual relation between two or more objects that generates a novel and meaningful concept, solution, method, explanation, or product. This article formally investigates into the cognitive process of creation and creativity as one of the most fantastic life functions. The cognitive foundations of creativity are explored in order to explain the space of creativity, the approaches to creativity, the relationship between creation and problem solving, and the common attributes of inventors. A set of mathematical models of creation and creativity is established on the basis of the tree structures and properties of human knowledge known as concept trees. The measurement of creativity is quantitatively analyzed, followed by the formal elaboration of the cognitive process of creation as a part of the Layered Reference Model of the Brain (LRMB).

On the Cognitive Processes of Human Perception with Emotions, Motivations, and Attitudes

2009 ◽  
pp. 141-153
Author(s):  
Yingxu Wang
Keyword(s):  
Software Engineering ◽  
Mathematical Models ◽  
Real Time ◽  
Cognitive Processes ◽  
Reference Model ◽  
Human Perception ◽  
Comprehensive Model ◽  
Time Process ◽  
Rigorous Model ◽  
The Brain

An interactive motivation-attitude theory is developed based on the Layered Reference Model of the Brain (LRMB) and the object-attributerelation (OAR) model. This paper presents a rigorous model of human perceptual processes such as emotions, motivations, and attitudes. A set of mathematical models and formal cognitive processes of perception is developed. Interactions and relationships between motivation and attitude are formally described in real-time process algebra (RTPA). Applications of the mathematical models of motivations and attitudes in software engineering are demonstrated. This work is a part of the formalization of LRMB, which provides a comprehensive model for explaining the fundamental cognitive processes of the brain and their interactions. This work demonstrates that the complicated human emotional and perceptual phenomena can be rigorously modeled and formally treated based on cognitive informatics theories and denotational mathematics.

On the Cognitive Processes of Human Perception with Emotions, Motivations, and Attitudes

2009 ◽  
pp. 685-697
Author(s):  
Yingxu Wang
Keyword(s):  
Software Engineering ◽  
Mathematical Models ◽  
Real Time ◽  
Cognitive Processes ◽  
Reference Model ◽  
Human Perception ◽  
Comprehensive Model ◽  
Time Process ◽  
Rigorous Model ◽  
The Brain

An interactive motivation-attitude theory is developed based on the Layered Reference Model of the Brain (LRMB) and the object-attributerelation (OAR) model. This paper presents a rigorous model of human perceptual processes such as emotions, motivations, and attitudes. A set of mathematical models and formal cognitive processes of perception is developed. Interactions and relationships between motivation and attitude are formally described in real-time process algebra (RTPA). Applications of the mathematical models of motivations and attitudes in software engineering are demonstrated. This work is a part of the formalization of LRMB, which provides a comprehensive model for explaining the fundamental cognitive processes of the brain and their interactions. This work demonstrates that the complicated human emotional and perceptual phenomena can be rigorously modeled and formally treated based on cognitive informatics theories and denotational mathematics.

The Theoretical Framework of Cognitive Informatics

2009 ◽  
pp. 33-59
Author(s):  
Yingxu Wang
Keyword(s):  
Cognitive Processes ◽  
Autonomic Computing ◽  
Knowledge Engineering ◽  
Reference Model ◽  
Human Perception ◽  
Theoretical Framework ◽  
Cognitive Informatics ◽  
Rigorous Treatment ◽  
Almost All ◽  
The Brain

Cognitive Informatics (CI) is a transdisciplinary enquiry of the internal information processing mechanisms and processes of the brain and natural intelligence shared by almost all science and engineering disciplines. This article presents an intensive review of the new field of CI. The structure of the theoretical framework of CI is described encompassing the Layered Reference Model of the Brain (LRMB), the OAR model of information representation, Natural Intelligence (NI) vs. Artificial Intelligence (AI), Autonomic Computing (AC) vs. imperative computing, CI laws of software, the mechanism of human perception processes, the cognitive processes of formal inferences, and the formal knowledge system. Three types of new structures of mathematics, Concept Algebra (CA), Real-Time Process Algebra (RTPA), and System Algebra (SA), are created to enable rigorous treatment of cognitive processes of the brain as well as knowledge representation and manipulation in a formal and coherent framework. A wide range of applications of CI in cognitive psychology, computing, knowledge engineering, and software engineering has been identified and discussed.

scholarly journals Pulverizing the Monopoly of Mind: Three Roles of the Body in Cognition

2019 ◽  
Vol 11 (1) ◽  
pp. 19-29
Author(s):  
Akhil Kumar Singh
Keyword(s):  
Cognitive Processes ◽  
Cognitive Abilities ◽  
Cognitive Process ◽  
The Body ◽  
Central Position ◽  
Computational Process ◽  
Internal Representations ◽  
The Brain ◽  
Basic Level ◽  
The Doors

For many decades, cognition has been viewed as a computational process in the brain. For cognition, the brain, body and the interaction with the environment are important. Conventional views are inclined towards the existence of discrete and internal representations realised by highly specific mechanisms in the brain. The Embodied approach challenges this view and accepts the evolution of cognitive abilities.  There is a shift in focus from the belief that the brain is solely responsible for cognition to the thought that the body is somehow deeply integrated into cognition. However, it does not deny the central position of the brain in the process of cognition but opens the doors for other factors for integration. At the basic level, there are three ways in which an agent’s body can be utilised for the cognitive process. An agent’s body may help to generate, operate and distribute the cognitive processes. As a result, this approach tries to diminish the monopoly of the brain by taking into account the importance of the body and the environment for cognition.

On Cognitive Foundations of Creativity and the Cognitive Process of Creation

2011 ◽  
pp. 284-297 ◽  
Author(s):  
Yingxu Wang
Keyword(s):  
Problem Solving ◽  
Cognitive Process ◽  
Reference Model ◽  
Human Beings ◽  
Inference Problem ◽  
Tree Structures ◽  
Structures And Properties ◽  
Cognitive Foundations ◽  
The Relationship ◽  
The Brain

Creativity is a gifted ability of human beings in thinking, inference, problem solving, and product development. A creation is a new and unusual relation between two or more objects that generates a novel and meaningful concept, solution, method, explanation, or product. This article formally investigates into the cognitive process of creation and creativity as one of the most fantastic life functions. The cognitive foundations of creativity are explored in order to explain the space of creativity, the approaches to creativity, the relationship between creation and problem solving, and the common attributes of inventors. A set of mathematical models of creation and creativity is established on the basis of the tree structures and properties of human knowledge known as concept trees. The measurement of creativity is quantitatively analyzed, followed by the formal elaboration of the cognitive process of creation as a part of the Layered Reference Model of the Brain (LRMB).

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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