Generative Forensics: Procedural Generation and Information Games
This addresses replayability issues for players and designers in mystery games, but it is incremental as it builds on existing procedural generation concepts.
The paper tackles the problem of spoilers and limited replayability in information games by introducing generative forensics games, where players analyze outputs from generative systems, and reports on prototypes evaluated from player and designer perspectives.
Procedural generation is used across game design to achieve a wide variety of ends, and has led to the creation of several game subgenres by injecting variance, surprise or unpredictability into otherwise static designs. Information games are a type of mystery game in which the player is tasked with gathering knowledge and developing an understanding of an event or system. Their reliance on player knowledge leaves them vulnerable to spoilers and hard to replay. In this paper we introduce the notion of generative forensics games, a subgenre of information games that challenge the player to understand the output of a generative system. We introduce information games, show how generative forensics develops the idea, report on two prototype games we created, and evaluate our work on generative forensics so far from a player and a designer perspective.