Failure and resilience are important aspects of gameplay. This is especially important for serious and competitive games, where players need to adapt and cope with failure frequently. In such situations, emotion regulation -- the active process of modulating ones' emotions to cope and adapt to challenging situations -- becomes essential. It is one of the prominent aspects of human intelligence and promotes mental health and well-being. While there has been work on developing artificial emotional regulation assistants to help users cope with emotion regulation in the field of Intelligent Tutoring systems, little is done to incorporate such systems or ideas into (serious) video games. In this paper, we introduce a data-driven 6-phase approach to establish empathetic artificial intelligence (EAI), which operates on raw chat log data to detect key affective states, identify common sequences and emotion regulation strategies and generalizes these to make them applicable for intervention systems.

翻译：失败与韧性是游戏玩法的核心要素，尤其在严肃游戏和竞技类游戏中尤为关键——玩家需要频繁适应并应对失败。在此类情境下，情绪调节——即主动调控自身情绪以应对和适应挑战性情境的过程——变得不可或缺。作为人类智能的重要特征之一，它促进心理健康与幸福感的提升。尽管智能辅导系统领域已有研究开发人工情绪调节助手以帮助用户应对情绪调节，但将此类系统或理念融入（严肃）电子游戏的工作仍非常有限。本文提出一种数据驱动的六阶段方法，用于构建共情型人工智能（EAI）。该系统基于原始聊天日志数据，通过检测关键情感状态、识别常见序列与情绪调节策略，并对其进行泛化处理，使其适用于干预系统。