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:失灵和应变能力是游戏游戏的重要方面。 这对于严肃而有竞争力的游戏来说尤其重要,因为玩家需要经常适应和应对失败。 在这种情况下,情感调控 -- -- 调节自己情感以适应和适应富有挑战性的局势的积极过程 -- -- 变得至关重要。这是人类智能的突出方面之一,促进心理健康和福祉。虽然一直在努力开发人工情感调控助理,以帮助用户应对智能教学系统领域的情绪调控,但在将这类系统或想法纳入(严重)视频游戏方面却做得很少。在本文中,我们引入了以数据驱动的六阶段方法,以建立同情性人工智能(EAI),该方法以原始聊天记录数据操作,以检测关键感官状态,确定共同序列和情感调控策略,并把这些策略推广到干预系统。