Social Story Worlds With Comme il Faut

Abstract

This paper presents Comme il Faut (CiF), an artificial intelligence system that matches character performances to appropriate social context, with the goal of enabling authors to write high-level rules governing expected character behavior in given social situations, rather than specific fixed choice points in a curated narrative structure. CiF models characters with a complex set of traits, feelings, and relationships, who can form intents, take actions, relate to a shared cultural space, and remember and refer to past events. A set of authored rules encoding appropriate behavior within a specific story world allow these characters to select actions to take (and respond to actions by others) in a manner consistent with their own personal and social concerns as well as a shifting interpersonal context. Through the development and release of Prom Week, a complete game using CiF as its narrative engine, we show how the system successfully creates complex narratives that are unique for each player and directed by those players' attempts to make progress towards story goals. We also show how CiF continues to be used in several in-progress interactive experiences (Mismanor and IMMERSE), speaking to the utility and flexibility of its design.