监管
发表于 2025-3-21 18:02:11
书目名称Applications of Evolutionary Computation影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0159394<br><br> <br><br>书目名称Applications of Evolutionary Computation读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0159394<br><br> <br><br>
Cabinet
发表于 2025-3-21 21:12:39
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Anthrp
发表于 2025-3-22 02:17:23
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豪华
发表于 2025-3-22 08:27:41
0302-9743 onal Conference on the Applications of Evolutionary Computation, EvoApplications 2011, held in Torino, Italy, in April 2011 colocated with the Evo* 2011 events. Thanks to the large number of submissions received, the proceedings for EvoApplications 2011 are divided across two volumes (LNCS 6624 and
迎合
发表于 2025-3-22 08:56:26
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Mingle
发表于 2025-3-22 14:19:11
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充足
发表于 2025-3-22 20:28:56
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爱国者
发表于 2025-3-22 21:50:09
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精美食品
发表于 2025-3-23 03:48:11
Evolving Interesting Maps for a First Person Shooterlayers’ average fighting time. For that purpose, four different map representations are tested and compared. Results obtained showcase the clear advantage of some representations in generating interesting FPS maps and demonstrate the promise of the approach followed for automatic level design in that game genre.
Ordeal
发表于 2025-3-23 05:36:23
Training Neural Networks to Play Backgammon Variants Using Reinforcement Learningg and Neural Network function approximation we train agents that learn a game position evaluation function for these games. We show that the resulting agents significantly outperform the open-source program Tavli3D.