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dc.contributor.authorPerez Estrada, LE-
dc.contributor.authorGroen, D-
dc.contributor.authorRamirez-Marquez, JE-
dc.identifier.citationProcedia Computer Science, Vol. 108, pp. 205-214, 2017en_US
dc.description.abstractThe success of refugee support operations depends on the ability of humanitarian organizations and governments to deploy aid effectively. These operations require that decisions on resource allocation are made as quickly as possible in order to respond to urgent crises and, by antici-pating future developments, remain adequate as the situation evolves. Agent-based modeling and simulation has been used to understand the progression of past refugee crises, as well as a way to predict how new ones will unfold. In this work, we tackle the problem of refugee aid deployment as a variant of the Robust Facility Location Problem (RFLP). We present a serious video game that functions as an interface for an agent-based simulation run with data from past refugee crises. Having obtained good approximate solutions to the RFLP by implementing a game that frames the problem as a puzzle, we adapted its mechanics and interface to correspond to refugee situations. The game is intended to be played by both subject matter experts and the general public, as a way to crowd-source effective courses of action in these situations.en_US
dc.sourceInternational Conference on Computational Science-
dc.sourceInternational Conference on Computational Science-
dc.subjectSerious gamesen_US
dc.titleA Serious Video Game To Support Decision Making On Refugee Aid Deployment Policyen_US
dc.typeConference Paperen_US
Appears in Collections:Dept of Computer Science Research Papers

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