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Over the past couple of decades, virtual humans have been attracting more and more attention. Many applications including, video games, movies, and various training and tutoring systems have benefited from work in this area. While the visual quality of virtual agents has improved dramatically, their intelligence and socialization still needs improvement. In this paper, the authors present work towards endowing agents with social roles and exploiting Explanation-Based Learning (EBL) to enable them to acquire additional, contextual behaviors from other agents. These virtual humans are capable of learning and applying role related actions from multiple agents and only adopt behaviors that have been explained to them, meaning that their definition of a role may be a subset from one or more agents. This results in emergent behaviors in heterogeneous populations.
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