A possible worlds model of belief for state-space narrative planning

Alireza Shirvani, Stephen G. Ware, Rachelyn Farrell

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

28 Scopus citations

Abstract

What characters believe, how they act based on those beliefs, and how their beliefs are updated is an essential element of many stories. State-space narrative planning algorithms treat their search spaces like a set of temporally possible worlds. We present an extension that models character beliefs as epistemically possible worlds and describe how such a space is generated. We also present the results of an experiment which demonstrates that the model meets the expectations of a human audience.

Original languageEnglish
Title of host publicationProceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017
Pages101-107
Number of pages7
ISBN (Electronic)9781577357919
StatePublished - 2017
Event13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017 - Snowbird, Little Cottonwood Canyon, United States
Duration: Oct 5 2017Oct 9 2017

Publication series

NameProceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

Conference

Conference13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017
Country/TerritoryUnited States
CitySnowbird, Little Cottonwood Canyon
Period10/5/1710/9/17

Bibliographical note

Publisher Copyright:
Copyright © 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

ASJC Scopus subject areas

  • Visual Arts and Performing Arts
  • Artificial Intelligence

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