Learning and skill set formation: A structural examination of version upgrades, user visibility, and AI strategies
研究了多人在线游戏中玩家技能集的形成与演变，包括边做边学和从他人特征中学习，并通过政策模拟帮助游戏开发者设计版本升级、用户可见性和AI机器人策略以提升用户参与。
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.