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Titlebook: Learning and Intelligent Optimization; Second International Vittorio Maniezzo,Roberto Battiti,Jean-Paul Watson Conference proceedings 2008

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发表于 2025-3-21 20:04:14 | 显示全部楼层 |阅读模式
书目名称Learning and Intelligent Optimization
副标题Second International
编辑Vittorio Maniezzo,Roberto Battiti,Jean-Paul Watson
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Learning and Intelligent Optimization; Second International Vittorio Maniezzo,Roberto Battiti,Jean-Paul Watson Conference proceedings 2008
描述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
出版日期Conference proceedings 2008
关键词Artificial intelligence; algorithms; combinatorial optimization; learning; machine learning; optimization
版次1
doihttps://doi.org/10.1007/978-3-540-92695-5
isbn_softcover978-3-540-92694-8
isbn_ebook978-3-540-92695-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2008
The information of publication is updating

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Limited-Memory Techniques for Sensor Placement in Water Distribution Networks,nt technological challenge. We describe our experience developing and deploying both exact and heuristic algorithms for placing sensors in water distribution networks to mitigate against damage due intentional or accidental introduction of contaminants. The target computing platforms for this applic
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0302-9743 iques, and ways of using memory about algorithm behavior in the past to improve performance in the future. Intelligent learning schemes for mining the knowledge978-3-540-92694-8978-3-540-92695-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Stephen Remde,Peter Cowling,Keshav Dahal,Nic Colledge
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Vittorio Maniezzo,Roberto Battiti,Jean-Paul Watson
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