ELEA - Build your own Evolutionary Algorithm in your Browser

被引:0
作者
Wagner, Markus [1 ]
Kohlros, Erik [2 ]
Quantmeyer, Gerome [2 ]
Koetzing, Timo [2 ]
机构
[1] Monash Univ, Clayton, Vic, Australia
[2] Univ Potsdam, Hasso Plattner Inst, Portsmouth, England
来源
PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION | 2023年
关键词
Benchmarking; education; tool;
D O I
10.1145/3583133.3590723
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We provide an open source framework to experiment with evolutionary algorithms which we call Experimenting and Learning toolkit for Evolutionary Algorithms (ELEA). ELEA is browser-based and allows to assemble evolutionary algorithms using drag-anddrop, starting from a number of simple pre-designed examples, making the startup costs for employing the toolkit minimal. The designed examples can be executed and collected data can be displayed graphically. Further features include export of algorithm designs and experimental results as well as multi-threading. With the very intuitive user interface and the short time to get initial experiments going, this tool is especially suitable for explorative analyses of algorithms as well as for the use in classrooms.
引用
收藏
页码:519 / 522
页数:4
相关论文
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