Semantic representation of action games

نویسندگان

  • Costas Boletsis
  • Dimitra Chasanidou
  • Panagiotis Pandis
  • Katia Lida Kermanidis
چکیده

Player modeling is a crucial procedure for the user-oriented videogame design. For player modeling to be achieved, modeling domain knowledge is essential. Mastering the semantics of a domain is to learn the “language” of the domain. In the present study, two approaches to representing “words” are considered and analyzed comparatively. The first approach (“grid” representation) is based on the division of the game terrain as a grid, capturing in each cell the content-based information of the action game. The second approach (“holistic” representation) captures the contextual information in which the action takes place (life, score, shield, number of hit asteroids etc.). For the present comparative analysis, we use the action videogame SpaceDebris. We analyze the data using the classification algorithms J48, Naive Bayes, and SMO, as well as the Kmeans clustering and we compare the results in an attempt to identify the approach that represents the semantic space more reliably. The data acquired from the“grid” representation perform better, however the low value of the performance’s difference does not allow us to come to rock solid conclusions.

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تاریخ انتشار 2011