Abstract
Winning or losing a game session is the final consequence of a series of decisions and actions made during the game. The analysis and understanding of events, mistakes, and fluxes of a concrete game play may be useful for different reasons: understanding problems related to gameplay, data mining of specific situations, and even understanding educational and learning aspects in serious games. We introduce a novel approach based on provenance concepts in order to model and represent a game flux. We model the game data and map it to provenance to generate a provenance graph for analysis. As an example, we also instantiated our proposed conceptual framework and graph generation in a serious game, allowing developers and designers to identify possible mistakes and failures in gameplay design by analyzing the generated provenance graph from collected gameplay data.
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Kohwalter, T.C., Clua, E.G.W., Murta, L.G.P. (2013). Game Flux Analysis with Provenance. In: Reidsma, D., Katayose, H., Nijholt, A. (eds) Advances in Computer Entertainment. ACE 2013. Lecture Notes in Computer Science, vol 8253. Springer, Cham. https://doi.org/10.1007/978-3-319-03161-3_23
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DOI: https://doi.org/10.1007/978-3-319-03161-3_23
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