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Artificial Intelligence Techniques for Rational Decision Making (Advanced Information and Knowledge Processing) - Softcover
Críticas
“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)
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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.
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- VerlagSpringer
- Erscheinungsdatum2016
- ISBN 10 3319382985
- ISBN 13 9783319382982
- EinbandTapa blanda
- Anzahl der Seiten184
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Artificial Intelligence Techniques for Rational Decision Making (Advanced Information and Knowledge Processing) by Marwala, Tshilidzi [Paperback ]
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Artificial Intelligence Techniques for Rational Decision Making
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ISBN 10: 3319382985
ISBN 13: 9783319382982
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9783319382982
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Zustand: New. Series: Advanced Information and Knowledge Processing. Num Pages: 183 pages, 35 black & white illustrations, 18 black & white tables, biography. BIC Classification: KJT; PBT; UYQ; UYQV. Category: (P) Professional & Vocational. Dimension: 159 x 237 x 15. Weight in Grams: 290. . 2016. Softcover reprint of the original 1st ed. 2014. Paperback. . . . . Bestandsnummer des Verkäufers V9783319382982
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Artificial Intelligence Techniques for Rational Decision Making
Verlag:
Springer International Publishing, 2016
ISBN 10: 3319382985
ISBN 13: 9783319382982
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9783319382982
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