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Serious Gaming for Predictive Analytics

Title: Serious Gaming for Predictive Analytics
Authors: Roderick M. Riensche; Patrick R. Paulson; Gary R. Danielson; Stephen D. Unwin; R. Scott Butner; Sarah M. Miller; Lyndsey R. Franklin; Nino Zuljevic
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://aaaipress.org/Papers/Symposia/Spring/2009/SS-09-09/SS09-09-020.pdf.
Collection: CiteSeerX
Description: We describe a methodology and architecture to support the development of games in a predictive analytics context. These games serve as part of an overall family of systems designed to gather input knowledge, calculate results of complex predictive technical and social models, and explore those results in an engaging fashion. The games provide an environment shaped and driven in part by the outputs of the models, allowing users to exert influence over a limited set of parameters, and displaying the results when those actions cause changes in the underlying model. We have crafted a prototype system in which we are implementing test versions of games driven by models in such a fashion, using a flexible architecture to allow for future continuation and expansion of this work.
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.470.1528
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.470.1528; http://aaaipress.org/Papers/Symposia/Spring/2009/SS-09-09/SS09-09-020.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.6C3397AC
Database: BASE