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A Knowledge Representation for Planning-Based Story Generation Applied to the Manual and Automatic Encoding of Plot

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Interactive Storytelling (ICIDS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11869))

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Abstract

There have been a range of coding schemes to code story structure. However, few of these coding schemes map directly to expressive formal models of story that also characterize character beliefs or the complexities that arise when mistaken beliefs lead to action failure. We describe HeadCode, a coding scheme motivated by recent work in plan-based story generation.

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Authors and Affiliations

  1. University of Utah, Salt Lake City, UT, USA

    Rushit Sanghrajka & R. Michael Young

Authors
  1. Rushit Sanghrajka
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  2. R. Michael Young
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Corresponding author

Correspondence to R. Michael Young .

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Editors and Affiliations

  1. University of Utah, Salt Lake City, UT, USA

    Rogelio E. Cardona-Rivera

  2. Georgia Institute of Technology, Atlanta, GA, USA

    Anne Sullivan

  3. University of Utah, Salt Lake City, UT, USA

    R. Michael Young

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Sanghrajka, R., Young, R.M. (2019). A Knowledge Representation for Planning-Based Story Generation Applied to the Manual and Automatic Encoding of Plot. In: Cardona-Rivera, R., Sullivan, A., Young, R. (eds) Interactive Storytelling. ICIDS 2019. Lecture Notes in Computer Science(), vol 11869. Springer, Cham. https://doi.org/10.1007/978-3-030-33894-7_31

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  • DOI: https://doi.org/10.1007/978-3-030-33894-7_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33893-0

  • Online ISBN: 978-3-030-33894-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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