Ahsum Nimity: exploring the possibilities of crowdsourcing Bayesian network structure learning through a video game

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dc.contributor.advisorRooij, I.J.E.I. van
dc.contributor.advisorVervuurt, W.
dc.contributor.advisorVelikova, M.
dc.contributor.authorRekké, S.T.
dc.date.issued2012-02-29
dc.description.abstractGames With A Purpose (GWAPs) are new and promising research tools that apply human-based computation through computer games. Human-based computation is a technique in which part of a computational problem is delegated to humans. Several GWAPs, such as the Foldit game, have shown that in some cases human players can produce good solutions to hard problems. The present research explores the possibility of developing a GWAP for applying human-based computation to such a problem: Bayesian network structure learning. Bayesian networks (BNs) are versatile graphical probabilistic models that are employed in a wide range of fields, both for practical applications and research. They encode knowledge about variables and their (in)dependencies, allowing probabilistic inference and reasoning under uncertainty. Unfortunately, learning the structure of BNs from data is NP-complete. In the present research a first attempt is made at crowdsourcing Bayesian network structure learning through a computer game. Keywords: Game With A Purpose (GWAP), human-based computation, crowdsourcing, Bayesian network (BN), structure learningen_US
dc.identifier.urihttp://theses.ubn.ru.nl/handle/123456789/198
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationMaster Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeMasteren_US
dc.titleAhsum Nimity: exploring the possibilities of crowdsourcing Bayesian network structure learning through a video gameen_US
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