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Identification And Classification Of Player Types In Massive Multiplayer Online Games Using Avatar Behavior, Earl M. Bednar
Identification And Classification Of Player Types In Massive Multiplayer Online Games Using Avatar Behavior, Earl M. Bednar
Theses and Dissertations
The purpose of our research is to develop an improved methodology for classifying players (identifying deviant players such as terrorists) through multivariate analysis of data from avatar characteristics and behaviors in massive multiplayer online games (MMOGs). To build our classification models, we developed three significant enhancements to the standard Generalized Regression Neural Networks (GRNN) modeling method. The first enhancement is a feature selection technique based on GRNNs, allowing us to tailor our feature set to be best modeled by GRNNs. The second enhancement is a hybrid GRNN which allows each feature to be modeled by a GRNN tailored to its …