Computational Intelligence Systems and Applications
By:Marian B. Gorzalczany
Published on 2001-12-14 by Springer Science & Business Media
Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge |buried| in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge |encoded| in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed.
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Book ID of Computational Intelligence Systems and Applications's Books is N3rpAZ09U70C, Book which was written byMarian B. Gorzalczanyhave ETAG "ZfbtG7sv9rs"
Book which was published by Springer Science & Business Media since 2001-12-14 have ISBNs, ISBN 13 Code is 9783790814392 and ISBN 10 Code is 3790814393
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