A good story is one in a million: Solution density in narrative generation problems

Cory Siler, Stephen G. Ware

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Narrative generation systems can be classified on a spectrum from strong autonomy to strong story. Systems on the strong autonomy side treat characters as fully independent agents but may struggle to meet the author’s requirements, while those on the strong story side direct character behaviors centrally but may struggle to create the illusion of character believability. In this paper, we use benchmark story generation problems as a framework to compare the spaces of stories that could be generated by prototypical strong story and strong autonomy systems. Comparing the relative solution densities of these spaces helps us quantify how common certain desirable narrative properties are. This can be informative for system designers when deciding, for instance, whether to strictly enforce all desired properties or to generate and filter from a broader class of solutions.

Original languageEnglish
Title of host publicationProceedings of the 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2020
EditorsLevi Lelis, David Thue
Pages123-129
Number of pages7
ISBN (Electronic)9781577358497
StatePublished - 2020
Event16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2020 - Virtual, Online
Duration: Oct 19 2020Oct 23 2020

Publication series

NameProceedings of the 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2020

Conference

Conference16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2020
CityVirtual, Online
Period10/19/2010/23/20

Bibliographical note

Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

This material is based upon work supported by the National Science Foundation under Grant No. IIS-1911053.

FundersFunder number
National Science Foundation (NSF)IIS-1911053

    ASJC Scopus subject areas

    • Visual Arts and Performing Arts
    • Artificial Intelligence

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