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Learning and Intelligent Optimization - Second International Conference, LION 2007 II, Trento, Italy, December 8-12, 2007. Selected Papers (Paperback, 2008 ed.) Loot Price: R1,397
Discovery Miles 13 970
Learning and Intelligent Optimization - Second International Conference, LION 2007 II, Trento, Italy, December 8-12, 2007....

Learning and Intelligent Optimization - Second International Conference, LION 2007 II, Trento, Italy, December 8-12, 2007. Selected Papers (Paperback, 2008 ed.)

Vittorio Maniezzo, Roberto Battiti, Jean-Paul Watson

Series: Theoretical Computer Science and General Issues, 5313

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Loot Price R1,397 Discovery Miles 13 970 | Repayment Terms: R131 pm x 12*

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This volume collects the accepted papers presented at the Learning and Intelligent OptimizatioN conference (LION 2007 II) held December 8-12, 2007, in Trento, Italy. The motivation for the meeting is related to the current explosion in the number and variety of heuristic algorithms for hard optimization problems, which raises - merous interesting and challenging issues. Practitioners are confronted with the b- den of selecting the most appropriate method, in many cases through an expensive algorithm configuration and parameter-tuning process, and subject to a steep learning curve. Scientists seek theoretical insights and demand a sound experimental meth- ology for evaluating algorithms and assessing strengths and weaknesses. A necessary prerequisite for this effort is a clear separation between the algorithm and the expe- menter, who, in too many cases, is "in the loop" as a crucial intelligent learning c- ponent. Both issues are related to designing and engineering ways of "learning" about the performance of different techniques, and ways of using memory about algorithm behavior in the past to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained from different runs or during a single run can - prove the algorithm development and design process and simplify the applications of high-performance optimization methods. Combinations of algorithms can further improve the robustness and performance of the individual components provided that sufficient knowledge of the relationship between problem instance characteristics and algorithm performance is obtained.

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Theoretical Computer Science and General Issues, 5313
Release date: December 2008
First published: 2008
Editors: Vittorio Maniezzo • Roberto Battiti • Jean-Paul Watson
Dimensions: 235 x 155 x 13mm (L x W x T)
Format: Paperback
Pages: 243
Edition: 2008 ed.
ISBN-13: 978-3-540-92694-8
Categories: Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 3-540-92694-1
Barcode: 9783540926948

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