Intelligent Problem Solving. Methodologies and Approaches: 13th International Conference on Industrial and Engineering Applications of Artificial Inte 2000 Edition Contributor(s): Logananthara, Rasiah (Editor), Palm, Günther (Editor), Ali, Moonis (Editor) |
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ISBN: 3540676899 ISBN-13: 9783540676898 Publisher: Springer OUR PRICE: $104.49 Product Type: Paperback - Other Formats Published: June 2000 |
Additional Information |
BISAC Categories: - Computers | Intelligence (ai) & Semantics |
Dewey: 006.3 |
LCCN: 00044016 |
Series: Lecture Notes in Computer Science |
Physical Information: 1.57" H x 6.14" W x 9.21" (2.39 lbs) 754 pages |
Descriptions, Reviews, Etc. |
Publisher Description: The focus of the papers presented in these proceedings is on employing various methodologies and approaches for solving real-life problems. Although the mechanisms that the human brain employs to solve problems are not yet completely known, we do have good insight into the functional processing performed by the human mind. On the basis of the understanding of these natural processes, scientists in the field of applied intelligence have developed multiple types of artificial processes, and have employed them successfully in solving real-life problems. The types of approaches used to solve problems are dependant on both the nature of the problem and the expected outcome. While knowledge-based systems are useful for solving problems in well-understood domains with relatively stable environments, the approach may fail when the domain knowledge is either not very well understood or changing rapidly. The techniques of data discovery through data mining will help to alleviate some problems faced by knowledge-based approaches to solving problems in such domains. Research and development in the area of artificial intelligence are influenced by opportunity, needs, and the availability of resources. The rapid advancement of Internet technology and the trend of increasing bandwidths provide an opportunity and a need for intelligent information processing, thus creating an excellent opportunity for agent-based computations and learning. Over 40% of the papers appearing in the conference proceedings focus on the area of machine learning and intelligent agents - clear evidence of growing interest in this area. |