集合(抽象数据类型)
计算机科学
能见度
用户参与度
人机交互
多媒体
人工智能
万维网
物理
光学
程序设计语言
摘要
For many multiplayer games, including massively multiplayer online role‐playing games, consumer skill sets with the game play an important role in engagement. Despite their importance, many aspects of consumers’ skill sets are still less well understood. This research considers the formation and evolution of players’ skill sets from two perspectives: (1) learning‐by‐doing, in which a consumer gradually improves his or her skill set with the game from past experiences with other players, and (2) learning about matched players’ skill sets from their observed characteristics (i.e., learning‐about‐others). Using policy simulations, we further demonstrate how inferences of players’ latent skill sets could help game developers design strategies for better engagement, from the perspectives of version upgrades, targeted user visibility, and artificial intelligence–powered bots.
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