Learning and Intelligent Optimization: Second International Conference, LION 2007 II, Trento, Italy, December 8-12, 2007. Selected Papers

Β· Β·
Β· Springer
Π•Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½Π° ΠΊΠ½ΠΈΠ³Π°
243
Π‘Ρ‚Ρ€Π°Π½ΠΈΡ†ΠΈ
ΠžΡ†Π΅Π½ΠΊΠΈΡ‚Π΅ ΠΈ ΠΎΡ‚Π·ΠΈΠ²ΠΈΡ‚Π΅ Π½Π΅ са ΠΏΠΎΡ‚Π²ΡŠΡ€Π΄Π΅Π½ΠΈ  НаучСтС ΠΏΠΎΠ²Π΅Ρ‡Π΅

Всичко Π·Π° Ρ‚Π°Π·ΠΈ Π΅Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½Π° ΠΊΠ½ΠΈΠ³Π°

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.

ΠžΡ†Π΅Π½Π΅Ρ‚Π΅ Ρ‚Π°Π·ΠΈ Π΅Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½Π° ΠΊΠ½ΠΈΠ³Π°

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ΠœΠΎΠΆΠ΅Ρ‚Π΅ Π΄Π° ΡΠ»ΡƒΡˆΠ°Ρ‚Π΅ Π·Π°ΠΊΡƒΠΏΠ΅Π½ΠΈΡ‚Π΅ ΠΎΡ‚ Google Play Π°ΡƒΠ΄ΠΈΠΎΠΊΠ½ΠΈΠ³ΠΈ посрСдством ΡƒΠ΅Π± Π±Ρ€Π°ΡƒΠ·ΡŠΡ€Π° Π½Π° ΠΊΠΎΠΌΠΏΡŽΡ‚ΡŠΡ€Π° си.
Π•Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½ΠΈ Ρ‡Π΅Ρ‚Ρ†ΠΈ ΠΈ Π΄Ρ€ΡƒΠ³ΠΈ устройства
Π—Π° Π΄Π° Ρ‡Π΅Ρ‚Π΅Ρ‚Π΅ Π½Π° устройства с Π΅Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½ΠΎ мастило, ΠΊΠ°Ρ‚ΠΎ Π½Π°ΠΏΡ€ΠΈΠΌΠ΅Ρ€ Π΅Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½ΠΈΡ‚Π΅ Ρ‡Π΅Ρ‚Ρ†ΠΈ ΠΎΡ‚ Kobo, трябва Π΄Π° ΠΈΠ·Ρ‚Π΅Π³Π»ΠΈΡ‚Π΅ Ρ„Π°ΠΉΠ» ΠΈ Π΄Π° Π³ΠΎ ΠΏΡ€Π΅Ρ…Π²ΡŠΡ€Π»ΠΈΡ‚Π΅ Π½Π° устройството си. Π˜Π·ΠΏΡŠΠ»Π½Π΅Ρ‚Π΅ ΠΏΠΎΠ΄Ρ€ΠΎΠ±Π½ΠΈΡ‚Π΅ инструкции Π² ΠŸΠΎΠΌΠΎΡ‰Π½ΠΈΡ Ρ†Π΅Π½Ρ‚ΡŠΡ€, Π·Π° Π΄Π° ΠΏΡ€Π΅Ρ…Π²ΡŠΡ€Π»ΠΈΡ‚Π΅ Ρ„Π°ΠΉΠ»ΠΎΠ²Π΅Ρ‚Π΅ Π² ΠΏΠΎΠ΄Π΄ΡŠΡ€ΠΆΠ°Π½ΠΈΡ‚Π΅ Π΅Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½ΠΈ Ρ‡Π΅Ρ‚Ρ†ΠΈ.

ΠžΡ‰Π΅ ΠΎΡ‚ Vittorio Maniezzo

Подобни Π΅Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½ΠΈ ΠΊΠ½ΠΈΠ³ΠΈ