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Artificial Intelligence Techniques for Rational Decision Making (Advanced Information and Knowledge Processing) - Hardcover
Synopsis
Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence.
Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:
- Theory of the marginalization of irrelevant information
- Principal component analysis
- Independent component analysis
- Automatic relevance determination method
In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.
Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.
"synopsis" may belong to another edition of this title.
Review
“Each chapter introduces a topic, discusses the theory for implementing it, and then describes a use case and the results of its application. ... This is an important book. ... Copious references, several pages per chapter, provide voluminous background material for the curious reader.” (G. R. Mayforth, Computing Reviews, December, 2015)
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2014
- ISBN 10 3319114239
- ISBN 13 9783319114231
- BindingHardcover
- Number of pages183
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon's bounded rationality theory are flexible due to advanced signal processing techniques, Moore's Law and artificial intelligence.Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:Theory of the marginalization of irrelevant information Principal component analysis Independent component analysisAutomatic relevance determination methodIn addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas. 184 pp. Englisch. Seller Inventory # 9783319114231
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Condition: New. Artificial Intelligence Techniques for Rational Decision Making Series: Advanced Information and Knowledge Processing. Num Pages: 183 pages, 35 black & white illustrations, 18 black & white tables, biography. BIC Classification: PBT; UYQ. Category: (P) Professional & Vocational. Dimension: 241 x 163 x 16. Weight in Grams: 426. . 2014. Hardback. . . . . Seller Inventory # V9783319114231
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon's bounded rationality theory are flexible due to advanced signal processing techniques, Moore's Law and artificial intelligence.Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize theattainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:Theory of the marginalization of irrelevant information Principal component analysis Independent component analysisAutomatic relevance determination methodIn addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas. Seller Inventory # 9783319114231
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