Automated Generation of Conversational Non Player Characters
نویسندگان
چکیده
An integral part of social believability in role playing games is believability of non-player characters (NPC). In this paper we argue for the importance of believability in NPCs, even those that are completely outside of any pre-written quest or plot. We present NPCAgency, a system designed to generate many conversational NPCs as packaged narrative assets that can be shared and imported into various projects to increase story-world immersion. We believe such a system can help solve two problems. First, the authorial burden of the game designer is lessened, allowing renderings of large numbers of NPCs, each with their own unique background and conversation topics, all conforming to the norms of a predefined “universe”. Second, the immersive aspect of the game is heightened as the player can engage complex characters with lengthy dialogue affordances. We demonstrate the concept by generating fifty characters with attributes drawn from “Game of Thrones” (GOT) / “A Song of Ice and Fire” universe, and exporting them as Inform 7 code, a popular declarative interactive fiction (IF) programming language and authoring tool. A user study of thirty-seven Inform 7 programmers demonstrates that a 62% majority find the tool useful enough to consider for their own work. Further 70% said they would use the system to create “Game of Thrones” background characters for their own projects.
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