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Increasing Performance via Gamification in a Volunteer-Based Evolutionary Computation System

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications (IPMU 2018)

Abstract

Distributed computing systems can be created using volunteers, users who spontaneously, after receiving an invitation, decide to provide their own resources or storage to contribute to a common effort. They can, for instance, run a script embedded in a web page; thus, collaboration is straightforward, but also ephemeral, with resources depending on the amount of time the user decides to lend. This implies that the user has to be kept engaged so as to obtain as many computing cycles as possible. In this paper, we analyze a volunteer-based evolutionary computing system called NodIO with the objective of discovering design decisions that encourage volunteer participation, thus increasing the overall computing power. We present the results of an experiment in which a gamification technique is applied by adding a leader-board showing the top scores achieved by registered contributors. In NodIO, volunteers can participate without creating an account, so one of the questions we wanted to address was if the need to register would have a negative impact on user participation. The experiment results show that even if only a small percentage of users created an account, those participating in the competition provided around 90% of the work, thus effectively increasing the performance of the overall system.

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Acknowledgments

This work has been supported in part by: Ministerio español de Economía y Competitividad under projects TIN2014-56494-C4-3-P (UGR-EPHEMECH) and TIN2017-85727-C4-2-P (UGR-DeepBio).

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Correspondence to Mario García-Valdez .

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García-Valdez, M., Merelo Guervós, J.J., Lara, L., García-Sánchez, P. (2018). Increasing Performance via Gamification in a Volunteer-Based Evolutionary Computation System. In: Medina, J., Ojeda-Aciego, M., Verdegay, J., Perfilieva, I., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2018. Communications in Computer and Information Science, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-91479-4_29

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  • DOI: https://doi.org/10.1007/978-3-319-91479-4_29

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