In a recent interview, the interviewer asked me to briefly explain my PhD work. While showing him what I did, he intersected “that’s just like Genetic Algorithms, right?” – “Yes, I am actually working on Genetic Algorithms” – “But your curriculum said you worked on “Evolutionary Computation”

…

I can’t really blame him. The field of evolutionary computation (and bioinspired heuristics in general), is plagued by too many “cute/cool” names, such as “Ant Colony Optimization”, “Ant Clustering”, “Memetic Algorithms”, “Queen bee optimization”, “Cat Swarm Optimization”, that often say very little about the technique under them, and less about what other techniques are related.

These names are often the result of well intentioned researchers who want to relate their findings with their inspiration, or who think that a new cool name can bring in more attention, more people and more ideas to the field. But I feel that these names more hinder than help, by making it difficult for people not in the field to have a grasp of what is connected with what, and for people in the field to make sure that what they are doing was not already done by someone else with a different cool name.