MURAL - Maynooth University Research Archive Library

    An Empirical Investigation of How and Why Neutrality Affects Evolutionary Search

    Galvan, Edgar and Poli, Riccardo (2006) An Empirical Investigation of How and Why Neutrality Affects Evolutionary Search. Genetic and Evolutionary Computation Conference, GECCO 2006, Proceedings,. pp. 1149-1156.

    Download (2MB) | Preview

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    The effects of neutrality on evolutionary search have been considered in a number of interesting studies, the results of which, however, have been contradictory. Some researchers have found neutrality to be beneficial to aid evolution whereas others have argued that the presence of neutrality in the evolutionary process is useless. We believe that this confusion is due to several reasons: many studies have based their conclusions on performance statistics (e.g., on whether or not a system with neutrality could solve a particular problem faster than a system without neutrality) rather than a more in-depth analysis of population dynamics, studies often consider problems, representations and search algorithms that are relatively complex and so results represent the compositions of multiple effects (e.g., bloat or spurious attractors in genetic programming), there is not a single definition of neutrality and different studies have added neutrality to problems in radically different ways. In this paper, we try to shed some light on neutrality by addressing these problems. That is, we use the simplest possible definition of neutrality (a neutral network of constant fitness, identically distributed in the whole search space), we consider one of the simplest possible algorithms (a mutation based, binary genetic algorithm) applied to two simple problems (a unimodal landscape and a deceptive landscape), and analyse both performance figures and, critically, population flows from and to the neutral network and the basins of attraction of the optima.

    Item Type: Article
    Keywords: Neutrality; Search Space; Genetic Algorithms;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15435
    Identification Number:
    Depositing User: Edgar Galvan
    Date Deposited: 08 Feb 2022 13:28
    Journal or Publication Title: Genetic and Evolutionary Computation Conference, GECCO 2006, Proceedings,
    Publisher: ACM
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads