Reproducibility in Evolutionary Computation
This paper addresses the problem of reproducibility for researchers in the field of Evolutionary Computation.
This paper discusses reproducibility in Evolutionary Computation (EC), proposing a refined classification system based on ACM's badge system. It identifies cultural and technical barriers to reproducibility in EC and offers guidelines and tools to address them.
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 (https://dlnext.acm.org/journal/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.