Dynamic and Accelerated Partial Order Planning for Interactive Narratives

Xun Zhang, Bhuvana C. Inampudi, Norman I. Badler, Mubbasir Kapadia

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper explores new narrative generation paradigms for open world problems. We propose a speed-up variant of partial planner-accelerated partial order planner, that can automatically generate narratives for large plan spaces. To incorporate real-time free-form user interaction, a dynamic partial planning technique has been introduced to self-repair the narratives. We also propose a scalable and robust framework to craft open world narratives with minimal effort. Our approach enables content creators to craft complex open world narratives without explicitly authoring user interaction arcs. We tested our framework by developing multiple narratives with free-form interactions. Those narratives were used to test the robustness of the proposed planners.

Original languageEnglish (US)
Pages289-295
Number of pages7
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

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

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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