Scheduling Live Interactive Narratives with Mixed-Integer Linear Programming

Sasha Azad, Jingyang Xu, Haining Yu, Boyang Li
November 2017 AI for Design and Production, Interactive Drama and Story Generation, Authoring Tools, Dynamic Adaptation, Formal Models, Procedural Content Generation, Strategic Decision Making, Virtual/Augmented/Mixed Reality
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A story with three alternative plot choices that would not be accomodated by traditional temporal scheduling under uncertainty

Abstract

A live interactive narrative (LIN) is an experience where multiple players take on fictional roles and interact with real-world objects and actors to participate in a pre-authored narrative. Temporal properties of LINs are important to its viability and aesthetic quality and hence deserve special design consideration. In this paper, we tackle the largely overlooked problem of scheduling a multiplayer interactive narrative and propose the Live Interactive Narrative Scheduling Problem (LINSP), which handles reasoning under temporal uncertainty, resource scheduling, and non-linear plot choices. We present a mixed-integer linear programming formulation of the problem and empirically evaluates its scalability over large narrative instances.

Type
Conference paper
Publication
The 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE) 2017
real world interactive narratives scheduling resource constrained temporal uncertainty multiplayer plot choices mixed integer linear programming artificial intelligence
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Sasha Azad
Ph.D. Computer Science Candidate

Sasha Azad is a Ph.D. Computer Science candidate at NC State University. Her main research interests lie in the field of Human-Centered Artificial Intelligence, AI for Storytelling, AI for Social Simulation, and Computational Social Science.

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