Decision theory with imperfect information / Rafik A Aliev and Oleg H Huseynov.
Material type: TextPublication details: Singapore : World Scientific, ©2014.Description: xxii, 444 pa. : illustrations ; 24 cmISBN:- 9789814611039 (hardcover : alk. paper)
- 003.56 23 Al398
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Books | ISI Library, Kolkata | 003.56 Al398 (Browse shelf(Opens below)) | Available | 137099 |
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003.54 Y48 First course in information theory | 003.54015113 C166 Information and randomness | 003.54015113 C166 Information and randomness | 003.56 Al398 Decision theory with imperfect information / | 003.56 G977 Fuzzy information and decision processes | 003.56 Is79 Multi-criteria decision analysis : methods and software / | 003.56 K76 Decision making under uncertainty : |
Includes bibliographical references and index.
1. Theories of decision making under uncertainty --
2. Fuzzy logic and approximate reasoning --
3. Preferences framework --
4. Imperfect decision-relevant information --
5. Uncertainty measures in decision making --
6. Fuzzy logic-based decision theory with imperfect information --
7. Hierarchial models for decision making with imperfect information --
8. Decision making models without utility --
9. Behavioral decision making with combined states under imperfect information --
10. Decision making under unpreciated imperfect information --
11. The general theory of decisions --
12. Simulations and applications.
Every day decision making in complex human-centric systems are characterized by imperfect decision-relevant information. The principal problems with the existing decision theories are that they do not have capability to deal with situations in which probabilities and events are imprecise. In this book, we describe a new theory of decision making with imperfect information. The aim is to shift the foundation of decision analysis and economic behavior from the realm bivalent logic to the realm fuzzy logic and Z-restriction, from external modeling of behavioral decisions to the framework of combined states. This book will be helpful for professionals, academics, managers and graduate students in fuzzy logic, decision sciences, artificial intelligence, mathematical economics, and computational economics.
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