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Believable Non-Player Characters (NPCs) help motivate player engagement withnarrative-driven games. An important aspect of believable characters is theircontextually-relevant reactions to changing situations, which emotion oftendrives in humans. Therefore, giving NPCs "emotion" should enhance theirbelievability. For adoption in industry, it is important to create tooldevelopment processes to build NPCs "with emotion" that fit current developmentpractices. Psychological validity-the grounding in affective science-is anecessary quality for plausible emotion-driven NPC behaviours. ComputationalModels of Emotion (CMEs) are one solution because they use at least oneaffective theory/model in their design. However, CME development tends to beunder documented so that its processes seem unsystematic and poorly defined.This makes it difficult to reuse a CME's components, extend or scale them, orcompare CMEs. This work draws from software engineering to propose threemethods for acknowledging and limiting subjectivity in CME development toimprove their reusability, maintainability, and verifiability: a systematic,document analysis-based methodology for choosing a CME's underlying affectivetheories/models using its high-level design goals and design scope, whichcritically influence a CME's functional requirements; an approach fortransforming natural language descriptions of affective theories into atype-based formal model using an intermediate, second natural languagedescription refining the original descriptions and showing where and whatassumptions informed the formalization; and a literary character analysis-basedmethodology for developing acceptance test cases with known believablecharacters from professionally-crafted stories that do not rely on specific CMEdesigns. Development of EMgine, a game development CME for generating NPCemotions, shows these methods in practice.

Start Your EM(otion En)gine: Towards Computational Models of Emotion for Improving the Believability of Video Game Non-Player Characters