  We present a demonstration of Play What I Mean (PWIM): a novel, AI-supported
interaction technique for interactive emergent narrative (IEN) games and play
experiences. By assisting players in translating high-level gameplay intents
(expressed as short, unstructured text strings) into concrete game actions,
PWIM aims to support open-ended player input while mitigating the overwhelm
that players sometimes feel when confronting the large action spaces that
characterize IEN gameplay. In matching player intents to game actions, PWIM
makes use of an off-the-shelf sentence embedding model that is lightweight
enough to run locally on a player's device, and wraps this model in a simple
user interface that allows the player to work around occasional classification
errors.
