Believable Non-Player Characters (NPCs) are a crucial component of narrativedriven games, which offer rich player experiences (PX). The quality of these NPCs’ interactions with players motivates continuous engagement with the game, and often re-engagement after players stop playing. An important aspect of believable characters is their contextually-relevant reactions to changing situations, including those caused by player actions. In humans, this is frequently driven by emotion. The plausibility of NPCs’ reactions partially depends on their psychological validity. A Computational Model of Emotion (CME), grounded in emotion theories and/or from psychology, is one solution because they can compute which emotion an NPC might experience given the current game state. A CME’s chosen underlying theories should be a consequence of its high-level requirements. We present a methodology that uses a set of emotion theories and a game-oriented CME’s high-level requirements and design scope to produce a grounded judgment of which theories best support the requirements.

Citation (ACM)

Geneva M. Smith and Jacques Carette. 2023. Start Your EMgine—A Methodology for Choosing Emotion Theories for Computational Models of Emotion. Submitted January 11, 2023 to Entertainment Computing. Available at