Conceptual Structures Information Processing In Mind And Machine Pdf
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- Conceptual structures : information processing in mind and machine
- John F. Sowa
- Modularising the Complex Meta-Models in Enterprise Systems Using Conceptual Structures
- Conceptual Structures: Information Processing in Mind and Machine
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Conceptual structures : information processing in mind and machine
Information processing , the acquisition, recording , organization, retrieval, display, and dissemination of information. In recent years, the term has often been applied to computer-based operations specifically.
In popular usage, the term information refers to facts and opinions provided and received during the course of daily life: one obtains information directly from other living beings, from mass media, from electronic data banks, and from all sorts of observable phenomena in the surrounding environment. A person using such facts and opinions generates more information, some of which is communicated to others during discourse, by instructions, in letters and documents, and through other media.
Information organized according to some logical relationships is referred to as a body of knowledge, to be acquired by systematic exposure or study. Application of knowledge or skills yields expertise, and additional analytic or experiential insights are said to constitute instances of wisdom. Use of the term information is not restricted exclusively to its communication via natural language.
Information is also registered and communicated through art and by facial expressions and gestures or by such other physical responses as shivering.
Moreover, every living entity is endowed with information in the form of a genetic code. These information phenomena permeate the physical and mental world, and their variety is such that it has defied so far all attempts at a unified definition of information.
Interest in information phenomena increased dramatically in the 20th century, and today they are the objects of study in a number of disciplines , including philosophy, physics, biology, linguistics, information and computer science , electronic and communications engineering , management science , and the social sciences.
On the commercial side, the information service industry has become one of the newer industries worldwide. Almost all other industries—manufacturing and service—are increasingly concerned with information and its handling. This article touches on such concepts as they relate to information processing. In treating the basic elements of information processing, it distinguishes between information in analog and digital form, and it describes its acquisition, recording, organization, retrieval, display, and techniques of dissemination.
A separate article, information system , covers methods for organizational control and dissemination of information. Interest in how information is communicated and how its carriers convey meaning has occupied, since the time of pre-Socratic philosophers, the field of inquiry called semiotics , the study of signs and sign phenomena. Signs are the irreducible elements of communication and the carriers of meaning. The American philosopher, mathematician, and physicist Charles S.
Peirce is credited with having pointed out the three dimensions of signs, which are concerned with, respectively, the body or medium of the sign, the object that the sign designates, and the interpretant or interpretation of the sign. Peirce recognized that the fundamental relations of information are essentially triadic; in contrast, all relations of the physical sciences are reducible to dyadic binary relations.
Another American philosopher, Charles W. Morris , designated these three sign dimensions syntactic, semantic, and pragmatic , the names by which they are known today. Information processes are executed by information processors. For a given information processor, whether physical or biological, a token is an object, devoid of meaning, that the processor recognizes as being totally different from other tokens.
Objects that carry meaning are represented by patterns of tokens called symbols. The latter combine to form symbolic expressions that constitute inputs to or outputs from information processes and are stored in the processor memory. Information processors are components of an information system, which is a class of constructs.
An abstract model of an information system features four basic elements: processor, memory, receptor, and effector Figure 1. The memory stores symbolic expressions, including those that represent composite information processes, called programs. The two other components, the receptor and the effector , are input and output mechanisms whose functions are, respectively, to receive symbolic expressions or stimuli from the external environment for manipulation by the processor and to emit the processed structures back to the environment.
The power of this abstract model of an information-processing system is provided by the ability of its component processors to carry out a small number of elementary information processes: reading; comparing; creating, modifying, and naming; copying; storing; and writing.
The model, which is representative of a broad variety of such systems, has been found useful to explicate man-made information systems implemented on sequential information processors. Because it has been recognized that in nature information processes are not strictly sequential, increasing attention has been focused since on the study of the human brain as an information processor of the parallel type.
The cognitive sciences , the interdisciplinary field that focuses on the study of the human mind, have contributed to the development of neurocomputers, a new class of parallel, distributed-information processors that mimic the functioning of the human brain , including its capabilities for self-organization and learning.
So-called neural networks , which are mathematical models inspired by the neural circuit network of the human brain, are increasingly finding applications in areas such as pattern recognition , control of industrial processes, and finance, as well as in many research disciplines. In the late 20th century, information acquired two major utilitarian connotations. On the one hand, it is considered an economic resource, somewhat on par with other resources such as labour, material, and capital.
This view stems from evidence that the possession, manipulation, and use of information can increase the cost-effectiveness of many physical and cognitive processes. The rise in information-processing activities in industrial manufacturing as well as in human problem solving has been remarkable. Analysis of one of the three traditional divisions of the economy, the service sector , shows a sharp increase in information-intensive activities since the beginning of the 20th century.
By these activities accounted for half of the labour force of the United States. As an individual and societal resource, information has some interesting characteristics that separate it from the traditional notions of economic resources.
Unlike other resources, information is expansive, with limits apparently imposed only by time and human cognitive capabilities. Its expansiveness is attributable to the following: 1 it is naturally diffusive, 2 it reproduces rather than being consumed through use, and 3 it can be shared only, not exchanged in transactions. At the same time, information is compressible, both syntactically and semantically. Coupled with its ability to be substituted for other economic resources, its transportability at very high speeds, and its ability to impart advantages to the holder of information, these characteristics are at the base of such societal industries as research, education, publishing, marketing, and even politics.
Societal concern with the husbanding of information resources has extended from the traditional domain of libraries and archives to encompass organizational, institutional, and governmental information under the umbrella of information resource management. The second perception of information is that it is an economic commodity, which helps to stimulate the worldwide growth of a new segment of national economies—the information service sector.
Taking advantage of the properties of information and building on the perception of its individual and societal utility and value, this sector provides a broad range of information products and services.
By the market share of the U. However, the probable convergence of computers and television which constitutes a market share times larger than computers and its impact on information services, entertainment, and education are likely to restructure the respective market shares of the information industry.
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John F. Sowa
To rebalance human creativity with computational execution, meta-models have been broken down into components then coupled together by interfaces analogous to the software engineering principles found in object-oriented design. In Enterprise Architecture, the meta-models have been modularised into layers and levels that collectively describe how a business works. A study describes the benefits of this approach Bork, Add to Cart. Instant access upon order completion. Free Content. More Information.
PDF | On Jan 1, , John F. Sowa published Conceptual Structures: Information Processing in Mind and Machine The Systems Programming Series | Find.
Modularising the Complex Meta-Models in Enterprise Systems Using Conceptual Structures
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Conceptual Structures: Information Processing in Mind and Machine
The book Conceptual Structures: Information Processing in Mind and Machine surveyed the state of the art in artificial intelligence and cognitive science in the early s and outlined a cognitive architecture as a foundation for further research and development. The basic ideas stimulated a broad range of research that built on and extended the original topics. This paper reviews that architecture and compares it to four other cognitive architectures with their roots in the same era: Cyc, Soar, Society of Mind, and Neurocognitive Networks. The concluding section surveys the VivoMind Cognitive Architecture, which builds on and extends the original version presented in the CS book.
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Clancey Published Computer Science Artif. View via Publisher.
The purpose of this article is to analyze semantic relations based on graph-independent structural analysis in VocBench. The mix-method of deductive and inductive approach is adapted in operating the research methodology, especially for data collection. The research data are structural domains of semantic relations in ontologies. VocBench includes around concepts. The sample size is around concepts. Sampling technique used is the stratified random sampling.