Hierarchical PNF Networks - A Temporal Model of Events for the Representation and Dramatization of Storytelling

Abstract

Storytelling is an important feature in games and also other types of (semi) automated entertainment systems such as machinima and digital-TV. The majority of the current research in storytelling use precedence-based directed acyclic graphs, or even linear sequences, to model the ordering of events in a story. This approach makes it easier to plan, recognize and perform these events in real-time, but it is also too simple to represent complex human actions, which form the basis of the most interesting stories in this niche. PNF-Networks and Interval Scripting are frameworks to represent, recognize and perform human action that was proposed in the context of computer-aided theatre. In this paper we describe two extensions to this framework that were designed and developed to enable its use in larger scale storytelling systems: Hierarchical PNF-Networks and a template-based definition. Hierarchical PNF-Networks present lower complexity propagation heuristic while the definition language enables high-level and abstract description of the temporal structure of the actions and events that compose an interactive story or game.