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Knowledge Representation Techniques A Rough Set Approach 2006th Edition by Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas ISBN 3540335188 978-3540335184

SKU: BELL-2178826

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Knowledge Representation Techniques A Rough Set Approach 2006th Edition by Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas ISBN 3540335188 978-3540335184 instant download after payment.

Publisher: Springer

File Extension: PDF

File size: 3.59 MB

Pages: 336

Author: Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas

ISBN: 9783540335184, 3540335188

Language: English

Year: 2006

Product desciption

Knowledge Representation Techniques A Rough Set Approach 2006th Edition by Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas ISBN 3540335188 978-3540335184 by Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas 9783540335184, 3540335188 instant download after payment.

Knowledge Representation Techniques: A Rough Set Approach 2006th Edition by Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas - Ebook PDF Instant Download/Delivery: 3540335188, 978-3540335184

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Product details:

ISBN 10: 3540335188

ISBN 13: 978-3540335184

Author: Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas

1. 1 Background The basis for the material in this book centers around research done in an ongoing long-term project which focuses on the development of highly au- 1 tonomousunmannedaerialvehiclesystems. Theactualplatformwhichserves as a case study for the research in this book will be described in detail later in this chapter. Before doing that, a brief background of the motivations - hind this research will be provided. One of the main research topics in the project is knowledge representation and reasoning and its use in Uav pl- forms. A very strong constraint has been placed on the nature of research done in the project where theoretical results, to the greatest extent possible, should serve as a basis for tractable reasoning mechanisms for use in a fully deployed autonomous Uav operating under soft real-time constraints asso- ated with the types of mission scenarios envisioned. Considering that much of the work with knowledge representation in this context focuses on application domains where one can only hope for an incomplete characterization of such domains, this methodological constraint has proven to be quite challenging since, in essence, the focus is on tractable approximate and nonmonotonic reasoning systems. As is well known, until recently, nonmonotonic formalisms have had a notorious reputation for lack of tractable and scalable reasoning systems.

Front Matter
Introduction and Preliminaries
- Introduction
- 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
Back Matter

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Tags: Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron, Andrzej Szalas, Knowledge, Representation, Techniques, Rough, Set, Approach