Journal•ISSN: 1557-3958
International Journal of Cognitive Informatics and Natural Intelligence
IGI Global
About: International Journal of Cognitive Informatics and Natural Intelligence is an academic journal published by IGI Global. The journal publishes majorly in the area(s): Computer science & Cognition. It has an ISSN identifier of 1557-3958. Over the lifetime, 379 publications have been published receiving 5098 citations. The journal is also known as: Cognitive informatics and natural intelligence & IJCINI.
Topics: Computer science, Cognition, Cognitive model, Pattern recognition (psychology), Cognitive computing
Papers published on a yearly basis
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TL;DR: Three types of new structures of mathematics, Concept Algebra (CA), Real-Time Process Algebra and System Algebra, 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.
Abstract: 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 for- mal 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 represen- tation 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.
345 citations
TL;DR: The authors provide a critical survey of the literature on both the resulting representations i.e., argument diagramming techniques and on the various aspects of the automatic analysis process.
Abstract: In this paper, the authors consider argument mining as the task of building a formal representation for an argumentative piece of text. Their goal is to provide a critical survey of the literature on both the resulting representations i.e., argument diagramming techniques and on the various aspects of the automatic analysis process. For representation, the authors also provide a synthesized proposal of a scheme that combines advantages from several of the earlier approaches; in addition, the authors discuss the relationship between representing argument structure and the rhetorical structure of texts in the sense of Mann and Thompsons 1988 RST. Then, for the argument mining problem, the authors also cover the literature on closely-related tasks that have been tackled in Computational Linguistics, because they think that these can contribute to more powerful argument mining systems than the first prototypes that were built in recent years. The paper concludes with the authors' suggestions for the major challenges that should be addressed in the field of argument mining.
312 citations
TL;DR: A fundamental cognitive decision making process and its mathematical model, which is described as a sequence of Cartesian-product based selections is presented and a rigorous description of the decision process in real-time process algebra (RTPA) is provided.
Abstract: Decision making is one of the basic cognitive processes of human behaviors by which a preferred option or a course of actions is chosen from among a set of alternatives based on certain criteria. Decision theories are widely applied in many disciplines encompassing cognitive informatics, computer science, management science, economics, sociology, psychology, political science, and statistics. A number of decision strategies have been proposed from different angles and application domains such as the maximum expected utility and Bayesian method. However, there is still a lack of a fundamental and mathematical decision model and a rigorous cognitive process for decision making. This article presents a fundamental cognitive decision making process and its mathematical model, which is described as a sequence of Cartesian-product based selections. A rigorous description of the decision process in real-time process algebra (RTPA) is provided. Real-world decisions are perceived as a repetitive application of the fundamental cognitive process. The result shows that all categories of decision strategies fit in the formally described decision process. The cognitive process of decision making may be applied in a wide range of decision-based systems such as cognitive informatics, software agent systems, expert systems, and decision support systems.
239 citations
TL;DR: A formal theory for abstract concepts and knowledge manipulation known as concept algebra is presented, which is capable to deal with complex knowledge and software structures as well as their algebraic operations.
Abstract: Concepts are the most fundamental unit of cognition that carries certain meanings in expression, thinking, reasoning, and system modeling. In denotational mathematics, a concept is formally modeled as an abstract and dynamic mathematical structure that encapsulates attributes, objects, and relations. The most important property of an abstract concept is its adaptive capability to autonomously interrelate itself to other concepts. This article presents a formal theory for abstract concepts and knowledge manipulation known as “concept algebra.†The mathematical models of concepts and knowledge are developed based on the object-attribute-relation (OAR) theory. The formal methodology for manipulating knowledge as a concept network is described. Case studies demonstrate that concept algebra provides a generic and formal knowledge manipulation means, which is capable to deal with complex knowledge and software structures as well as their algebraic operations.
181 citations
TL;DR: The Object-Attribute-Relation model is presented to formally represent the structures of internal information and knowledge acquired and learned in the brain and the magnitude of human memory capacity is rigorously estimated on the basis of OAR.
Abstract: The cognitive models of information representation are fundamental research areas in cognitive informatics, which attempts to reveal the mechanisms and potential of the brain in learning and knowledge representation. Because memory is the foundation of all forms of natural intelligence, a generic model of memory, particularly the long-term memory, may explain the fundamental mechanism of internal information representation and the forms of learning results. This article presents the Object-Attribute-Relation (OAR) model to formally represent the structures of internal information and knowledge acquired and learned in the brain. The neural informatics model of human memory is introduced with particular focus on the long-term memory. Then, the OAR model that explains the mechanisms of internal knowledge and information representation in the brain is formally described, and the physical and physiological meanings of this model are explained. Based on the OAR model, knowledge structures and learning mechanisms are rigorously explained. Further, the magnitude of human memory capacity is rigorously estimated on the basis of OAR, by which the memory capacity is derived to be in the order of 10 8,432 bits.
137 citations