Narrative Planning Model Acquisition from Text Summaries and Descriptions

Thomas Hayton, Julie Porteous, João F. Ferreira, Alan Lindsay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

AI Planning has been shown to be a useful approach for the generation of narrative in interactive entertainment systems and games. However, the creation of the underlying narrative domain models is challenging: the well documented AI planning modelling bottleneck is further compounded by the need for authors, who tend to be non-technical, to create content. We seek to support authors in this task by allowing natural language (NL) plot synopses to be used as a starting point from which planning domain models can be automatically acquired. We present a solution which analyses input NL text summaries, and builds structured representations from which a PDDL model is output (fully automated or author in-theloop). We introduce a novel sieve-based approach to pronoun resolution that demonstrates consistently high performance across domains. In the paper we focus on authoring of narrative planning models for use in interactive entertainment systems and games. We show that our approach exhibits comprehensive detection of both actions and objects in the systemextracted domain models, in combination with significant improvement in the accuracy of pronoun resolution due to the use of contextual object information. Our results and an expert user assessment show that our approach enables a reduction in authoring effort required to generate baseline narrative domain models from which variants can be built.
Original languageEnglish
Title of host publicationProceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20)
PublisherAAAI press
Pages1709-1716
Number of pages8
Volume34 No.2
ISBN (Electronic)9781577358350
Publication statusPublished - 2020
Event34th AAAI Conference on Artificial Intelligence - Hilton New York Midtown, New York City, United States
Duration: 7 Feb 202012 Feb 2020
Conference number: 34
https://aaai.org/Conferences/AAAI-20/

Publication series

NameThe Thirty-Fourth Aaai Conference On Artificial Intelligence The Thirty-Second Innovative Applications Of Artificial Intelligence Conference The Tenth Aaai Symposium On Educational Advances In Artificial Intelligence
PublisherAAAI Press
Number2
Volume34
ISSN (Print)2159-5399
ISSN (Electronic)2374-3468

Conference

Conference34th AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI-20
CountryUnited States
CityNew York City
Period7/02/2012/02/20
Internet address

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  • Cite this

    Hayton, T., Porteous, J., Ferreira, J. F., & Lindsay, A. (2020). Narrative Planning Model Acquisition from Text Summaries and Descriptions. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) (Vol. 34 No.2, pp. 1709-1716). (The Thirty-Fourth Aaai Conference On Artificial Intelligence The Thirty-Second Innovative Applications Of Artificial Intelligence Conference The Tenth Aaai Symposium On Educational Advances In Artificial Intelligence; Vol. 34, No. 2). AAAI press.