This paper reports on an experiment in formalizing and implementing “story-sifting” heuristics to automatically identify likely “interesting stories” from a large mass of events transpiring from the Chroniqueur procedural social simulation. Following preliminary experimentation with various concepts inspired by narratology, we proceeded to formally evaluate “unexpectedness” and “dramatic situations” as key heuristics to sample six stories from a simulation run and rendered each as two short stories, one written by a human author and the other by a LLM (in order to help distinguish the effect of narrative from story). These were scored by 24 participants for narrative appreciation. Inconclusive results about heuristics making any significant difference prompted self-reflection on what makes emergent narratives interesting (in a distinct way from traditional fiction), pointing both at “story effects” (some selected event chains constituting better story material) and “narrative effect” (better narrativization being able to cope with poor story material).

There is a distinct pleasure in the discovery of an emergent story while interacting with a digital game. Most game interfaces, however, only allow this to happen in the here and now of play, and do not afford the retrieval of potentially interesting events that might have happened outside the player's view, or that were missed as they were occurring. We present our project's Chronicles interface that automatically documents most of what has transpired in the game world in a form inspired by Wikipedia. This allows players to intuitively explore entities and past events, facilitating the discovery of emergent stories. Because this represents a daunting mass of information, we conceptualize the notion of designed “entry points” to the data, i.e. suggestions and motivations to consult specific content. We also propose a subjective mode, disclosing only the information the player-character is aware of in order to maintain a meaningful economy of knowledge.

Emergent narratives provide a unique and compelling approach to interactive storytelling through simulation, and have applications in games, narrative generation, and virtual agents. However, the inherent complexity of simulation makes understanding the expressive potential of emergent narratives difficult, particularly at the design phase of development. In this article, we present a novel approach to emergent narrative using the narratological theory of possible worlds and demonstrate how the design of works in such a system can be understood through a formal means of analysis inspired by expressive range analysis. Last, we propose a novel way through which content may be authored for the emergent narrative system using a sketch-based interface.

Recent years have borne witness to an explosion of games research from diverse home disciplines. Much of this work concerns game design, but the games research community has yet to agree on practices and methods for examining game design that are simultaneously rigorously scholarly, flexible enough to accommodate a design-oriented perspective, and sufficiently knowledgeable of computation to engage with the materiality of games.

This paper reports on an ongoing attempt to develop an author-friendly approach to procedural game dialogue generation. Various affordances of the experimental authoring tool Expressionist are appropriated to allow non-computer scientist authors to design virtual characters' discourse and reasoning potential. The paper describes how the Hammurabi game project makes use of metadata-driven context free grammars to author virtual characters that can generate not only discourse but also context-relevant decisions. The author-friendliness and generativity of the approach is discussed.