Knowledge Representation Techniques
A Rough Set Approach
(Sprache: Englisch)
This book contains a cohesive, self-contained collection of theoretical and applied research results that have been achieved in this project which pertain to nonmonotonic and approximate easoning systems developed for an experimental unmanned aerial vehicle...
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Produktinformationen zu „Knowledge Representation Techniques “
This book contains a cohesive, self-contained collection of theoretical and applied research results that have been achieved in this project which pertain to nonmonotonic and approximate easoning systems developed for an experimental unmanned aerial vehicle system used in the project. This book should be of interest to the theoretician and applied researcher alike and to autonomous system developers and software agent and intelligent system developers.
Klappentext zu „Knowledge Representation Techniques “
The basis for the material in this book centers around a long term research project with autonomous unmanned aerial vehicle systems. One of the main research topics in the project is knowledge representation and reasoning. The focus of the research has been on the development of tractable combinations of approximate and nonmonotonic reasoning systems. The techniques developed are based on intuitions from rough set theory. Efforts have been made to take theory into practice by instantiating research results in the context of traditional relational database or deductive database systems. This book contains a cohesive, self-contained collection of many of the theoretical and applied research results that have been achieved in this project and for the most part pertain to nonmonotonic and approximate reasoning systems developed for an experimental unmanned aerial vehicle system used in the project. This book should be of interest to the theoretician and applied researcher alike and to autonomous system developers and software agent and intelligent system developers.
Inhaltsverzeichnis zu „Knowledge Representation Techniques “
Part I: Introduction and Preliminaries: Introduction- Basic Notion
- Rough Sets
- Relational and Deductive Databases
- Non-monotonic Reasoning
Part II: From Relations to Knowledge Representation
- Rough Knowledge Databases
- Combining Rough and Crisp Knowledge
- Weakest Sufficient and Strongest Necessary Conditions
- CAKE: Computer Aided Knowledge Engineering
- Formalization of Default Logic Using CAKE
- A UAV Scenario: A Case Study
Part III: From Sensors to Relations
- Information Granules
- Tolerance Spaces
- 14 A Rough Set Approach to Machine Learning
- UAV Learning Process: A Case Study
Bibliographische Angaben
- Autoren: Patrick Doherty , Witold Lukaszewicz , Andrzej Szalas
- 2006, 2006, VI, 334 Seiten, 55 Schwarz-Weiss-Abbildungen, Masse: 16,4 x 24,2 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3540335188
- ISBN-13: 9783540335184
- Erscheinungsdatum: 16.06.2006
Sprache:
Englisch
Rezension zu „Knowledge Representation Techniques “
From the reviews:"Knowledge representation is one of the most important elements of Artificial Intelligence, representing the study of how knowledge about the world can be represented and what kinds of reasoning can be done with that knowledge. The book contains three parts and is founded on the concept of rough sets. ... This book is recommended to researchers interested in studying and applying rough set theory in various domains." -- Ion Iancu, Zentralblatt MATH, Vol. 1131 (9), 2008
Pressezitat
From the reviews: "Knowledge representation is one of the most important elements of Artificial Intelligence, representing the study of how knowledge about the world can be represented and what kinds of reasoning can be done with that knowledge. The book contains three parts and is founded on the concept of rough sets. ... This book is recommended to researchers interested in studying and applying rough set theory in various domains." (Ion Iancu, Zentralblatt MATH, Vol. 1131 (9), 2008)
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