Applying planning to interactive storytelling: Narrative control using state constraints

Julie Porteous, Marc Cavazza, Fred Charles

Research output: Contribution to journalArticleResearchpeer-review

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Abstract

We have seen ten years of the application of AI planning to the problem of narrative generation in Interactive Storytelling (IS). In that time planning has emerged as the dominant technology and has featured in a number of prototype systems. Nevertheless key issues remain, such as how best to control the shape of the narrative that is generated (e.g., by using narrative control knowledge, i.e., knowledge about narrative features that enhance user experience) and also how best to provide support for real-time interactive performance in order to scale up to more realistic sized systems. Recent progress in planning technology has opened up new avenues for IS and we have developed a novel approach to narrative generation that builds on this. Our approach is to specify narrative control knowledge for a given story world using state trajectory constraints and then to treat these state constraints as landmarks and to use them to decompose narrative generation in order to address scalability issues and the goal of real-time performance in larger story domains. This approach to narrative generation is fully implemented in an interactive narrative based on the “Merchant of Venice.” The contribution of the work lies both in our novel use of state constraints to specify narrative control knowledge for interactive storytelling and also our development of an approach to narrative generation that exploits such constraints. In the article we show how the use of state constraints can provide a unified perspective on important problems faced in IS.
Original languageEnglish
Pages (from-to)1-21
JournalACM Transactions on Intelligent Systems and Technology
Volume1
Issue number2
DOIs
Publication statusPublished - Nov 2010

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Interactive Storytelling
Control Constraints
State Constraints
Planning
Scalability
Trajectories
Narrative
Interactive Narrative
Real-time
Scale-up
User Experience
Landmarks

Bibliographical note

ACM allows an authors' version of their own ACM-copyrighted work on their personal server or on servers belonging to their employers. For full details see http://www.acm.org/publications/policies/RightsResponsibilities [Accessed 05/01/2011]

Cite this

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abstract = "We have seen ten years of the application of AI planning to the problem of narrative generation in Interactive Storytelling (IS). In that time planning has emerged as the dominant technology and has featured in a number of prototype systems. Nevertheless key issues remain, such as how best to control the shape of the narrative that is generated (e.g., by using narrative control knowledge, i.e., knowledge about narrative features that enhance user experience) and also how best to provide support for real-time interactive performance in order to scale up to more realistic sized systems. Recent progress in planning technology has opened up new avenues for IS and we have developed a novel approach to narrative generation that builds on this. Our approach is to specify narrative control knowledge for a given story world using state trajectory constraints and then to treat these state constraints as landmarks and to use them to decompose narrative generation in order to address scalability issues and the goal of real-time performance in larger story domains. This approach to narrative generation is fully implemented in an interactive narrative based on the “Merchant of Venice.” The contribution of the work lies both in our novel use of state constraints to specify narrative control knowledge for interactive storytelling and also our development of an approach to narrative generation that exploits such constraints. In the article we show how the use of state constraints can provide a unified perspective on important problems faced in IS.",
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Applying planning to interactive storytelling: Narrative control using state constraints. / Porteous, Julie; Cavazza, Marc; Charles, Fred.

In: ACM Transactions on Intelligent Systems and Technology, Vol. 1, No. 2, 11.2010, p. 1-21.

Research output: Contribution to journalArticleResearchpeer-review

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