Analysis and Decision Making in Uncertain Systems
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A unified and systematic description of analysis and decision problems within a wide class of uncertain systems, described by traditional mathematical methods and by relational knowledge representations. With special emphasis on uncertain control systems, Prof. Bubnicki gives you an unique approach to stability and stabilization of uncertain systems.
- Self contained
- Introduction and development of original concepts of uncertain variables and a learning process consisting of knowledge validation and updating
- Examples concerning the control of manufacturing systems, assembly processes and task distributions in computer systems indicate the possibilities of practical applications and approaches to decision making in uncertain systems
- Includes special problems such as recognition and control of operations under uncertainty
If you are interested in problems of uncertain control systems and uncertain decision support systems, this will be a valuable addition to your bookshelf. Written for researchers and students in the field of control and information science, this book will also benefit designers of information and control systems.
- Self contained
- Introduction and development of original concepts of uncertain variables and a learning process consisting of knowledge validation and updating
- Examples concerning the control of manufacturing systems, assembly processes and task distributions in computer systems indicate the possibilities of practical applications and approaches to decision making in uncertain systems
- Includes special problems such as recognition and control of operations under uncertainty
If you are interested in problems of uncertain control systems and uncertain decision support systems, this will be a valuable addition to your bookshelf. Written for researchers and students in the field of control and information science, this book will also benefit designers of information and control systems.
Problems, methods and algorithms of decision making based on an uncertain knowledge now create a large and intensively developing area in the field of knowledge-based decision support systems. The main aim of this book is to present a unified, systematic description of analysis and decision problems in a wide class of uncertain systems described by traditional mathematical models and by relational knowledge representations. A part of the book is devoted to new original ideas introduced and developed by the author: the concept of uncertain variables and the idea of a learning process consisting in knowledge validation and updating. In a certain sense this work may be considered as an extension of the author's monograph Uncertain Logics, Variables and Systems (Springer-Verlag, 2002). In this book it has been shown how the different descriptions of uncertainty based on random, uncertain and fuzzy variables may be treated uniformly and applied as tools for general analysis and decision problems, and for specific uncertain systems and problems (dynamical control systems, operation systems, knowledge-based pattern recognition under uncertainty, task allocation in a set of multiprocessors with uncertain execution times, and decision making in an assembly system as an example of an uncertain manufacturing system). The topics and the organization of the text are presented in Chapter 1 (Sects 1. 1 and 1. 4). The material presented in the book is self-contained.
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