Knowledge structures for communications in human-computer systems : general automata-based
著者
書誌事項
Knowledge structures for communications in human-computer systems : general automata-based
Wiley, c2007
- : pbk
大学図書館所蔵 全4件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references (p. 273-277) and index
内容説明・目次
内容説明
A comprehensive look at General automata and how it can be used to establish the fundamentals for communication in human-computer systems
Drawing 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.
目次
Preface. 1. Introduction.
1.1 Considerations for Establishing Knowledge Structures for Computers.
1.2 Knowledge About Automata as a Subset of World Knowledge.
1.2.1 General Automata.
1.2.2 Extracting and Storing the Meanings of Sentences.
1.2.3 Associating Knowledge.
1.2.4 Establishing Conclusions and Inferences.
Exercises.
2. A General Automaton.
2.1 Formal Analysis for a General Automaton.
2.1.1 General Analysis.
2.1.2 Graph Model.
2.1.3 Select Properties of the Graph Model.
2.2 An Application of the Disciplines to the Modeling of Natural Automata.
2.2.1 A Case Study.
2.2.2 Required State Changes.
2.2.3 Algorithm for Determining Required State Changes.
Exercises.
3. A General Automaton: Detailed Analysis.
3.1 Distinguishable Receptors and Effectors.
3.2 Nonhomogeneous Environments.
3.3 Transformation Response Components.
3.4 Nonshared Environments Interpreted as Distinguishable.
3.4.1 Model for Performance in Both Shared and Nonshared Environments.
3.4.2 Model for Performance in Shared Environments.
Exercises.
4. Processing of Knowledge About Automata.
4.1 Formulation of a Language Information Theory.
4.1.1 Class 1 Sentence.
4.1.2 Class 2 Sentence.
4.1.3 Class 3 Sentence.
4.1.4 Class 4 Sentence.
4.1.5 Class 5 Sentence.
4.1.6 Class 6 Sentence.
4.1.7 Class 7 Sentence.
4.2 Extracting and Storing the Meaning of Sentences by Computer.
4.2.1 Description of an Algorithm.
4.3 Knowledge Association.
4.3.1 Association by Combining Graphs Through Common Points.
4.3.2 Associations by Combining Graph (n + 1)-Tuples.
4.3.3 Computer Methods for Association of Knowledge.
4.4 Deductive Processes.
4.4.1 Deductive Processes Related to Association Through Common Points.
4.4.2 Deductive Processes Related to Association by Combining Graph Tuples.
4.4.3 Deductive Processes with Aristotelian Form A as a Premise.
4.5 Inferences.
4.5.1 Inferences Related to a Single Graph Tuple of Associated Knowledge.
4.5.2 Inferences Related to More than One Graph Tuple of Associated Knowledge.
Exercises.
5. A General System of Interactive Automata.
5.1 Formal Analysis for a General System of Interactive Automata.
5.1.1 General Analysis.
5.1.2 Microsystem Model.
5.1.3 Macrosystem Model.
5.2 Example Applications.
5.2.1 A Two-Component System.
5.2.2 A System of Many Components.
Exercises.
6. Processing of Knowledge About Systems of Automata.
6.1 A General System of Interactive Automata: Detailed Analysis.
6.1.1 The Microsystem Model.
6.1.2 The Macrosystem Model.
6.2 Knowledge Structures for Sentences Describing Systems of Interactive Automata.
Exercises.
7. Changing Expressions of Knowledge for Communication from One Form and Style to Another.
7.1 Introduction.
7.2 Sets and Relations.
7.3 Establishing Open Expressions and Open Sentences.
7.4 Selecting Subsets of Open Expressions.
7.5 Applying the Results of the Above Analysis.
7.6 Summary and Conclusions.
Exercises.
8. Electronic Security Through Pseudo Languages.
8.1 Introduction.
8.2 Defi nitions, Sets, and Relations.
8.3 Analysis for E-Security Through Pseudo Languages.
8.3.1 A Basic E-Security System.
8.3.2 A Two-Step Encryption System.
8.3.3 E-Signing.
8.4 Summary and Conclusions.
Exercises.
Appendix A: Analysis for an Effective Operation of a General Automaton.
A.1 Introduction.
A.2 Recursive Methods.
A.3 Effective Operation Analysis.
Exercises.
Appendix B: Analysis for an Effective Operation of a General System of Interactive Automata.
B.1 Introduction.
B.2 Microsystem Graphs.
B.3 Macrosystem Graphs.
B.4 Example.
Exercises.
References.
Index.
「Nielsen BookData」 より