Uncertainty in computational intelligence-based decision making /

Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model constructio...

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Bibliografiske detaljer
Andre forfattere: Ahmadian, Ali (Editor)
Format: Electronisk eBog
Sprog:engelsk
Udgivet: London ; San Diego, CA ; Cambridge, MA : Academic Press, [2025]
Serier:Advanced studies in complex systems.
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Online adgang:ScienceDirect
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082 0 4 |a 003/.54  |2 23/eng/20241016  |1 https://id.oclc.org/worldcat/ddc/E3YpHVcwJ8JpChrvfbJPYvGTmD 
245 0 0 |a Uncertainty in computational intelligence-based decision making /  |c edited by Ali Ahmadian, [and three others]. 
264 1 |a London ;  |a San Diego, CA ;  |a Cambridge, MA :  |b Academic Press,  |c [2025] 
264 4 |c ©2025 
300 |a 1 online resource (xvi, 322 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Advanced Studies in Complex Systems 
504 |a Includes bibliographical references and index. 
588 |a Description based on online resource; title from digital title page (viewed on November 13, 2024). 
520 |a Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others.The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science. - Provides readers a thorough understanding of the uncertainty that arises in artificial intelligence (AI), computational intelligence (CI) paradigms, and algorithms - Encourages readers to put concepts into practice and solve complex real-world problems using CI development frameworks like decision support systems and visual decision design - Provides a comprehensive overview of the techniques used in computational intelligence, uncertainty, and decision. 
650 0 |a Uncertainty (Information theory) 
650 0 |a Decision making  |x Data processing. 
650 0 |a Computational intelligence. 
650 6 |a Incertitude (Théorie de l'information)  |0 (CaQQLa)201-0003328 
650 6 |a Prise de décision  |0 (CaQQLa)201-0007575  |x Informatique.  |0 (CaQQLa)201-0380011 
650 6 |a Intelligence informatique.  |0 (CaQQLa)201-0265216 
650 7 |a Computational intelligence  |2 fast  |0 (OCoLC)fst00871995 
650 7 |a Decision making  |x Data processing  |2 fast  |0 (OCoLC)fst00889041 
650 7 |a Uncertainty (Information theory)  |2 fast  |0 (OCoLC)fst01160838 
700 1 |a Ahmadian, Ali,  |e editor.  |1 https://id.oclc.org/worldcat/entity/E39PCjGVCJ4mMr9fm4BMwkyhf3 
776 0 8 |i Print version:  |z 0443214751  |z 9780443214752  |w (OCoLC)1424739644 
830 0 |a Advanced studies in complex systems. 
856 4 0 |3 ScienceDirect  |u https://www.sciencedirect.com/science/book/9780443214752