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Uncertainty in Computational Intelligence-Based Decision Making

Part of the Advanced Studies in Complex Systems series
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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.

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Published 01/09/2024
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Product Details
Academic Press Inc
0443214751 / 9780443214752
Paperback / softback
006.31
01/09/2024
United States
English
350 pages
24 cm