descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Other literature type 13 Oct 2021Embargo end date: 01 Jan 2021 English Publisher:Association for Computing Machinery (ACM)Journal:ACM Transactions on Evolutionary Learning and Optimization, volume 1, pages 1-21 (issn: 2688-299X, eissn: 2688-3007,

Authors: Manuel López-ibáñez; Juergen Branke; Luís Paquete;

doi: 10.1145/3466624 , 10.48550/arxiv.2102.03380

arXiv: http://arxiv.org/abs/2102.03380

Reproducibility in Evolutionary Computation

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Abstract

Experimental studies are prevalent in Evolutionary Computation ( EC ), and concerns about the reproducibility and replicability of such studies have increased in recent times, reflecting similar concerns in other scientific fields. In this article, we discuss, within the context of EC, the different types of reproducibility and suggest a classification that refines the badge system of the Association of Computing Machinery ( ACM ) adopted by ACM Transactions on Evolutionary Learning and Optimization ( TELO ). We identify cultural and technical obstacles to reproducibility in the EC field. Finally, we provide guidelines and suggest tools that may help to overcome some of these reproducibility obstacles.

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Keywords

FOS: Computer and information sciences, Artificial Intelligence (cs.AI), TA, Computer Science - Artificial Intelligence, Optimization and Control (math.OC), FOS: Mathematics, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), Mathematics - Optimization and Control

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