Abstract

It has been hypothesized that sexual selection, in conjunction with sexual runaway effects, is the way nature discovers novelty. At the same time, the novelty search algorithm has been proposed as the computational means to effectively explore a solution space without using an objective fitness function. Here, the sexual selection algorithm is defined in such a way that it is largely compatible with novelty search so that it can be used in future applications. In comparison to novelty search, the sexual selection algorithm is capable of exploring the solution space more effectively. This work also supports the idea that sexual selection, disregarding possible confounding effects natural organisms might have, is a very effective way of finding novel adaptations in nature.

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