Knowledge Representation Techniques: A Rough Set Approach: Studies in Fuzziness and Soft Computing, cartea 202
Autor Patrick Doherty, Witold Lukaszewicz, Andrzej Szalasen Limba Engleză Hardback – 16 iun 2006
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Specificații
ISBN-13: 9783540335184
ISBN-10: 3540335188
Pagini: 345
Ilustrații: VI, 334 p.
Dimensiuni: 210 x 297 x 29 mm
Greutate: 0.67 kg
Ediția:2006
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540335188
Pagini: 345
Ilustrații: VI, 334 p.
Dimensiuni: 210 x 297 x 29 mm
Greutate: 0.67 kg
Ediția:2006
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
and Preliminaries.- Basic Notions.- Rough Sets.- Relational and Deductive Databases.- Non-Monotonic Reasoning.- 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.- From Sensors to Relations.- Information Granules.- Tolerance Spaces.- A Rough Set Approach to Machine Learning.- UAV Learning Process: A Case Study.
Recenzii
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)
"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)
Textul de pe ultima copertă
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.
Caracteristici
Most important feature of our book is a new methodology and new methods for approximate reasoning leading from experimental knowledge (e.g. sensor measurements) to conclusions in natural language. The new results include foundations of our approach built using rough set approach for inducing concept approximations and reasoning with them, methods for embadding background knowledge as well as non-monotonic reasoning in reasoning engines of intelligent systems Readers interested in constructing intelligent systems can learn a novel methodology crucial for development of such systems