Evaluating the effectiveness and applicability of Novelty Search and other Quality-Diversity algorithms compared to niching

Abstract

Novelty Search is a promising new evolutionary algorithm, which claims to outperform traditional evolutionary algorithms in some cases. The idea is that sometimes, pursuing the objective, like in traditional evolutionary algorithms, may prevent the objective from being reached. In these cases, it might be better to explore solutions that are inherently different than previous ones instead of solutions that have a higher fitness value. Imagine walking through a maze towards a goal, but first having to walk away from it to eventually reach it. The question is how effective this method is compared to niching algorithms, another methods that tries to increase both quality and diversity. In this paper we will subject novelty search and niching algorithms to the classic maze experiment, in order to find out exactly how effective novelty search is when compared to niching and in what cases.