We present Why Are We Like This?(WAWLT), a mixed-initiative, co-creative storytelling
game in which two players develop a story transcript by selecting and editing actions to …

Story sifting, also known as story recognition, has been identified as one of the major design
challenges currently facing interactive emergent narrative. However, despite continued …

We propose a new approach to the human-centered evaluation of AI-based games,
grounded in the analysis of player retellings of their play experiences. Retellings offer …

Large language models (LLMs) enabled by the datasets and computing power of the last
decade have recently gained popularity for their capacity to generate plausible natural …

A distinctive aspect of interactive stories is how they enable players to impact the story
based on their choices, with repeated playthroughs potentially yielding different stories …

Story sifters attempt to automatically or semi-automatically extract nuggets of compelling
narrative content from vast chronicles of game or simulation events. Though sifting has …

The use of computation in archaeology is a kind of magic, a way of heightening the
archaeological imagination. Agent-based modelling allows archaeologists to test the 'just …

This paper presents a case study in the experience-first prototyping of a generative game.
Our goal in this process was to create a PCG-based mystery story construction game …

We trace the history of emergent narrative as both a term and a concept, with a particular
focus on interactive emergent narrative (IEN): the use of emergent narrative as an approach …

The task of selecting a subset of story-worthy events from out of an observed collection of
facts–known as story sifting–is a useful human ability that has yet to be emulated …