A comprehensive look at General automata and how it can be used to establish the fundamentals for communication in human-computer systemsDrawing on author Eldo C. Koenig's extensive expertise and culling from his thirty-four previously published works, this seminal resource presents knowledge structures for communication in Human-Computer Systems (HCS) based on General automata. The resulting model provides knowledge representations for software engineering.Of the many features required for a method to achieve the desired communication in HCS, Knowledge Structures for Communications in Human-Computer Systems identifies six of them in great length-extracting and storing the knowledge of sentences; knowledge association; deductive processes; inferences; feedback; and sequencing of knowledge-along with illustrations for achieving them by the General Automata Method. After presenting the analysis for each feature, the book includes practical applications that illustrate the results. Koenig also describes algorithms and programs that achieve some of the features, and provides readers with additional algorithms and further research.Richly illustrated throughout to elucidate concepts, Knowledge Structures for Communications in Human-Computer Systems is an excellent teaching text suitable for both academic and industrial settings.
Author(s): Eldo C. Koenig
Edition: 1
Year: 2006
Language: English
Pages: 281
KNOWLEDGE STRUCTURES FOR COMMUNICATIONS IN HUMAN-COMPUTER SYSTEMS......Page 3
CONTENTS......Page 9
Preface......Page 13
1.1 Considerations for Establishing Knowledge Structures for Computers......Page 15
1.2 Knowledge About Automata as a Subset of World Knowledge......Page 16
1.2.1 General Automata......Page 18
1.2.2 Extracting and Storing the Meanings of Sentences......Page 20
1.2.3 Associating Knowledge......Page 23
1.2.4 Establishing Conclusions and Inferences......Page 28
Exercises......Page 31
2.1.1 General Analysis......Page 33
2.1.2 Graph Model......Page 42
2.1.3 Select Properties of the Graph Model......Page 55
2.2 An Application of the Disciplines to the Modeling of Natural Automata......Page 62
2.2.1 A Case Study......Page 63
2.2.2 Required State Changes......Page 66
2.2.3 Algorithm for Determining Required State Changes......Page 72
Exercises......Page 74
3.1 Distinguishable Receptors and Effectors......Page 77
3.2 Nonhomogeneous Environments......Page 81
3.3 Transformation Response Components......Page 84
3.4 Nonshared Environments Interpreted as Distinguishable......Page 85
3.4.1 Model for Performance in Both Shared and Nonshared Environments......Page 86
3.4.2 Model for Performance in Shared Environments......Page 91
Exercises......Page 93
4. Processing of Knowledge About Automata......Page 95
4.1 Formulation of a Language Information Theory......Page 96
4.1.1 Class 1 Sentence......Page 100
4.1.2 Class 2 Sentence......Page 103
4.1.3 Class 3 Sentence......Page 107
4.1.4 Class 4 Sentence......Page 108
4.1.5 Class 5 Sentence......Page 112
4.1.6 Class 6 Sentence......Page 115
4.1.7 Class 7 Sentence......Page 116
4.2 Extracting and Storing the Meaning of Sentences by Computer......Page 117
4.2.1 Description of an Algorithm......Page 118
4.3 Knowledge Association......Page 119
4.3.1 Association by Combining Graphs Through Common Points......Page 122
4.3.2 Associations by Combining Graph (n+1)-Tuples......Page 124
4.3.3 Computer Methods for Association of Knowledge......Page 126
4.4.1 Deductive Processes Related to Association Through Common Points......Page 127
4.4.2 Deductive Processes Related to Association by Combining Graph Tuples......Page 131
4.4.3 Deductive Processes with Aristotelian Form A as a Premise......Page 134
4.5.1 Inferences Related to a Single Graph Tuple of Associated Knowledge......Page 138
4.5.2 Inferences Related to More than One Graph Tuple of Associated Knowledge......Page 148
Exercises......Page 150
5.1.1 General Analysis......Page 153
5.1.2 Microsystem Model......Page 163
5.1.3 Macrosystem Model......Page 170
5.2.1 A Two-Component System......Page 176
5.2.2 A System of Many Components......Page 185
Exercises......Page 187
6.1 A General System of Interactive Automata: Detailed Analysis......Page 189
6.1.2 The Macrosystem Model......Page 190
6.2 Knowledge Structures for Sentences Describing Systems of Interactive Automata......Page 191
Exercises......Page 198
7.1 Introduction......Page 199
7.2 Sets and Relations......Page 201
7.3 Establishing Open Expressions and Open Sentences......Page 203
7.4 Selecting Subsets of Open Expressions......Page 207
7.5 Applying the Results of the Above Analysis......Page 209
7.6 Summary and Conclusions......Page 213
Exercises......Page 216
8.1 Introduction......Page 217
8.2 Definitions, Sets, and Relations......Page 218
8.3.1 A Basic E-Security System......Page 219
8.3.2 A Two-Step Encryption System......Page 222
8.3.3 E-Signing......Page 226
Exercises......Page 227
A.1 Introduction......Page 229
A.2 Recursive Methods......Page 230
A.3 Effective Operation Analysis......Page 250
Exercises......Page 255
B.1 Introduction......Page 257
B.2 Microsystem Graphs......Page 262
B.3 Macrosystem Graphs......Page 274
B.4 Example......Page 285
Exercises......Page 286
References......Page 287
Index......Page 293
