Theory of Knowledge: Structures and Processes

950 Pages·2017·9.146 MB·English

by  Mark Burgin

Vol. 5
World Scientific Series in Information Studies —
Theory of
Knowledge
Structures and Processes
Mark Burgin
University of California, Los Angeles, USA
World Scientific
Published by
World Scientific Publishing Co. Pte. Ltd.
5 Toh Tuck Link, Singapore 596224
USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601
UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE
Library of Congress Cataloging-in-Publication Data
Names: Burgin, M. S. (Mark Semenovich), author.
Title: Theory of knowledge : structures and processes / Mark Burgin.
Description: New Jersey : World Scientific, 2016. | Series: World Scientific series in information
studies ; Volume 5 | Includes bibliographical references and index.
Identifiers: LCCN 2015049963 | ISBN 9789814522670 (hc : alk. paper)
Subjects: LCSH: Knowledge, Theory of.
Classification: LCC BD161 .B865 2216 | DDC 121--dc23
LC record available at http://lccn.loc.gov/2015049963
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library.
Copyright © 2017 by World Scientific Publishing Co. Pte. Ltd.
Printed in Singapore
September27,2016 19:41 TheoryofKnowledge:StructuresandProcesses-9inx6in b2334-fm pagev
Contents
Preface ix
Acknowledgments xiii
About the Author xv
1. Introduction 1
1.1. The role of knowledge in the contemporary
society . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2. A brief history of knowledge studies . . . . . . . . . . 9
1.3. Structure of the book . . . . . . . . . . . . . . . . . . 39
2. Knowledge Characteristics and Typology 45
2.1. The differentiation and classification of knowledge . . 45
2.2. Existential characteristics of knowledge . . . . . . . . 77
2.3. Descriptive properties of knowledge
and corresponding typology . . . . . . . . . . . . . . . 91
2.3.1. Dimensions and other characteristics
of knowledge . . . . . . . . . . . . . . . . . . . 94
2.3.2. Correctness, relevance, and consistency
of knowledge . . . . . . . . . . . . . . . . . . . 96
2.3.3. Confidence in and certainty of knowledge . . . 119
2.3.4. Complexity and clarity of knowledge . . . . . . 122
2.3.5. Significance of knowledge . . . . . . . . . . . . 131
2.3.6. Efficiency of knowledge . . . . . . . . . . . . . 134
2.3.7. Reliability of knowledge . . . . . . . . . . . . . 136
2.3.8. Abstractness and generality of knowledge . . . 137
2.3.9. Completeness of knowledge versus precision
of knowledge . . . . . . . . . . . . . . . . . . . 139
2.3.10. Meaning of knowledge . . . . . . . . . . . . . . 140
2.3.11. Other descriptive properties of knowledge . . . 149
2.4. Metaknowledge and metadata . . . . . . . . . . . . . . 151
3. Knowledge Evaluation and Validation
in the Context of Epistemic Structures 169
3.1. Knowledge in the context of epistemic structures
and knowledge scales . . . . . . . . . . . . . . . . . . . 170
3.2. Knowledge evaluation, justification, and testing . . . . 215
3.2.1. Knowledge evaluation . . . . . . . . . . . . . . 215
3.2.2. Knowledge validation, justification,
and testing . . . . . . . . . . . . . . . . . . . . 240
3.3. Local consistency versus global consistency
in knowledge representation . . . . . . . . . . . . . . . 263
4. Knowledge Structure and Functioning:
Microlevel or Quantum Theory of Knowledge 307
4.1. Basic structures of knowledge units on the quantum
level — knowledge quanta and semantic links . . . . . 309
4.1.1. Quantum theory of knowledge (QTK) . . . . . 310
4.1.2. Semantic link network theory (SLNT) and
Semantic link theory of knowledge (SLTK) . . 329
4.1.3. QTK–SLTK connection . . . . . . . . . . . . . 340
4.2. Signs and symbols as quantum units of knowledge . . 343
4.3. Operations with and relations between quantum
knowledge units . . . . . . . . . . . . . . . . . . . . . . 358
4.3.1. Properties of and relations between nodes
and links in SLN and knowledge quanta
in QTK . . . . . . . . . . . . . . . . . . . . . . 360
4.3.2. Operations with extended knowledge
quanta . . . . . . . . . . . . . . . . . . . . . . 369
4.3.3. Operations with symbolic knowledge quanta
and complete semantic links . . . . . . . . . . 380
5. Knowledge Structure and Functioning:
Macrolevel or Theory of Average Knowledge 395
5.1. Language as a universal tool for knowledge
representation . . . . . . . . . . . . . . . . . . . . . . . 402
5.1.1. Natural languages . . . . . . . . . . . . . . . . 403
5.1.2. Languages of science and mathematics . . . . . 411
5.1.3. Algorithmic and programming languages . . . 423
5.2. Logic as a tool for knowledge representation
and production . . . . . . . . . . . . . . . . . . . . . . 428
5.2.1. Concepts, names, terms, and objects . . . . . . 446
5.2.2. Statements, queries, and instructions . . . . . 481
5.2.3. Logical systems of inference . . . . . . . . . . . 491
5.3. Theory of abstract properties . . . . . . . . . . . . . . 500
5.4. Semantic networks and ontology . . . . . . . . . . . . 518
5.5. Scripts and productions . . . . . . . . . . . . . . . . . 527
5.6. Frames and Schemas . . . . . . . . . . . . . . . . . . . 536
6. Knowledge Structure and Functioning:
Megalevel or Global Theory of Knowledge 593
6.1. A typology of structures and scientific knowledge . . . 595
6.2. Nuclear and comprehensive knowledge systems . . . . 603
6.3. Logic-linguistic knowledge system and descriptive
knowledge . . . . . . . . . . . . . . . . . . . . . . . . . 612
6.4. Model-representation knowledge system and
representational knowledge . . . . . . . . . . . . . . . 617
6.5. Procedural, axiological and instrumental
knowledge systems, and operational knowledge . . . . 622
6.6. Relations between and operations with global
knowledge systems . . . . . . . . . . . . . . . . . . . . 631
6.7. Hierarchies of knowledge systems . . . . . . . . . . . . 636
7. Knowledge Production, Acquisition,
Engineering, and Application 643
7.1. Knowledge production, learning, and acquisition
as basic cognitive processes . . . . . . . . . . . . . . . 644
7.1.1. Scientific cognition . . . . . . . . . . . . . . . . 658
7.1.2. Intuition as a cognitive instrument . . . . . . . 669
7.1.3. Computers and networks as cognitive tools . . 688
7.1.4. Learning . . . . . . . . . . . . . . . . . . . . . 696
7.1.5. Knowledge creation in organizations . . . . . . 705
7.2. Knowledge organization and engineering . . . . . . . . 711
7.3. Knowledge management and application . . . . . . . . 714
8. Knowledge, Data, and Information 721
8.1. Epistemic structures and cognitive information . . . . 722
8.2. Structural aspects of knowledge–information
duality . . . . . . . . . . . . . . . . . . . . . . . . . . . 727
8.3. Information as a source of knowledge . . . . . . . . . . 760
8.4. Dynamic aspects of knowledge, data, and
information interaction . . . . . . . . . . . . . . . . . . 766
8.5. Knowledge as a measure of information . . . . . . . . 791
9. Conclusion 803
Appendix 809
A. Set theoretical foundations . . . . . . . . . . . . . . . 809
B. Elements of the theory of algorithms . . . . . . . . . . 819
C. Elements of algebra and category theory . . . . . . . . 825
D. Numbers and numerical functions . . . . . . . . . . . . 831
E. Topological, metric and normed spaces . . . . . . . . . 833
Bibliography 837
Subject Index 927
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Preface
If the extent of...knowledge is the hallmark of our civilization,
the use to be made of it may be its crisis.
S. Dilon Ripley
An investment in knowledge pays the best interest.
Benjamin Franklin
Knowledge has always been important in society and all educated
people have always understood importance of knowledge. That is
why Western philosophers have studied knowledge as an important
phenomenon from the time of Plato and Aristotle. Thinkers from
other countries, such as China and India, also tried to understand
the essence of knowledge from ancient times.
In contemporary society, importance of knowledge is much higher
and continues to grow very fast. Researchers concluded that knowl-
st
edge had become the key strategic asset for the 21 century and
for every organization. Consequently, the necessity in developing the
best strategy for identifying, developing, and applying the knowl-
edgeassets has becomecritical. Everyorganization needstoinvest in
creating and implementing the best knowledge networks, processes,
methods, tools, and technologies.
Thegrowingneedsinknowledgeandefficientknowledgeorganiza-
tion intensifiedstudies of knowledge. Therearethreemain directions
in these studies:
— The philosophical and methodological direction, which comprises
epistemology and the methodology of science and mathematics.
— The area of artificial intelligence (AI), in which knowledge is
perceived as the base of intelligence.
— The field of knowledge management where knowledge is treated
as the main asset of companies and organizations.
AI is typically directed at knowledge representation and
processing.
Epistemology is largely interested in knowledge definition and
acquisition (cognition).
Knowledge management is mostly concerned with knowledge
organization and utilization.
In addition, knowledge is also explored in psychology, sociology,
and linguistics.
Intensification of studies in area of knowledge brought forth a
quantity of books on a variety of issues and problems of knowledge.
So, why is this book different? It is different because its main goal is
to present, organize and synthesize the basic ideas, results, and con-
cepts from these three directions, which are loosely related now, into
a unified theory of knowledge and knowledge processes. It is called
the synthetic theory of knowledge. It is multidisciplinary and trans-
disciplinary at the same time. The approach presented in this book
provides a new explanation of important relations between knowl-

edge and information demonstrating new kinds of possibilities for
knowledge management, information technology, data mining, infor-
mation sciences, computer science, knowledge engineering, psychol-
ogy, social sciences, genetics, and education that are made available
by the synthetic theory of knowledge.
Explanation of knowledge essence, structure and functioning is
given in this book, as well as answers to the following questions:
— How knowledge is related to information and data?
— How knowledge is modeled by mathematical and logical
structures?
— How these models are used to better understand and utilize com-
putersandInternet,cognitionandeducation,communicationand
computation?
Knowledgeisinseparablefrominformation.Peopleacquireknowl-
edge receiving cognitive information. At the same time, knowledge,
by its essence, contains information and this is the main feature of
knowledge. This intrinsic unity of knowledge and information forms
the base of the synthetic theory of knowledge.
September27,2016 19:40 TheoryofKnowledge:StructuresandProcesses-9inx6in b2334-ch01 page1
Chapter 1
Introduction
All men by nature desire knowledge.
Aristotle
Thereis an abundanceof differentbooks and paperstreating various
problemsandstudyingdifferentissuesofknowledge(cf.,forexample,
(Aune, 1967; Polanyi, 1974; Cleveland, 1985; Chisholm, 1989; Bloor,
1991; Burgin, 1997; Boisot, 1998; Choo, 1998; Rao, 1998; Pollock
and Cruz, 1999; Bernecker and Dretske, 2000; Bean and Green,
2001; Popper,2002; Goldman, 2004; Dalkir, 2005; Leydesdorff, 2006;
Magnani, 2007; Nguen, 2008; Fantl and McGrath, 2009; Zhuge,
2012)). A lot of ideas, models, and several theories have been sug-
gested in this area. The whole area of knowledge related activities
consists of three parts:
1. Knowledge studies (theoretical and experimental).
2. Knowledge engineering.
3. Knowledge utilization and management.
Thetwo latter parts belongto knowledge technology — knowledge
engineering deals with technology of knowledge production, orga-
nization, transformation, management, preservation, capture and
acquisition, while knowledge utilization studies how people and orga-
nizations use knowledge, developing new techniques and approaches
for this purpose.
1