Paper Presentation: A Survey on Story Generation Techniques

B6ff5f798c18a3367b2770aa3ada0730?s=47 Chris
October 24, 2016

Paper Presentation: A Survey on Story Generation Techniques

This talk presents the findings of Kybartas and Bidarra in their survey paper on story generation techniques:



October 24, 2016


  1. A Survey on Story Generation Techniques for Authoring Computational Narratives

    Paper by Ben Kybartas and Rafael Bidarra Presentation by Chris Martens CSC 791: Generative Methods Monday, October 24, 2016 1
  2. Purpose of this paper 2 Q: What is the purpose

    of any survey paper?
  3. Purpose of this paper 3 Define common goals of a

    research community Review progress on those goals Classify progress along different axes Identify gaps for future work
  4. Human-Computer Collaboration 4 Which parts does the computer do? Which

    parts does the human do?
  5. Outline 5 Terminology Examples Classification Scheme Examples to Test

  6. Terminology 6

  7. 7

  8. 8

  9. 9

  10. Story vs. Space 10 Playwright vs. Director script: characters act

    structure scenes lines performance: actors props set delivery
  11. 11

  12. Plot Automation 12 Manual Structure Template Constrained Automated

  13. Plot Automation 13 Manual Structure Template Constrained Automated Computer is

    present at a mostly invisible level
  14. Plot Automation 14 Manual Structure Template Constrained Automated Computer is

    present at a mostly invisible level Attempts to minimize author involvement as much as possible
  15. 15 Examples

  16. 16 Manual Authoring Tools Interactive Fiction Creation Programming Education Therapy

  17. 17 Storyspace Twine Inform 7

  18. Scrivener 18

  19. 19 Plot Generation Systems Grammar-based Planning-based Other

  20. Grammars as Templates 20 Grammar describes an outline of the

    narrative but does not populate it with existents.
  21. Proppian Grammars 21

  22. Cohn Comic Grammars 22

  23. Grammars as Complete Plot Generators 23 GESTER: rules defining relations

    between existents TEATRIX: grammar as director, player as performer
  24. Grammars as Complete Plot Generators 24 GESTER

  25. ReGen: Story Graph Rewriting 25

  26. Planning-Based Systems 26 Story Canvas

  27. Porteous et al. “Applying planning to interactive storytelling” 27

  28. Case-Based Reasoning 28 Engage/Reflect Cycle Reflection uses a corpus of

    previous stories to evaluate and revise the current story on the basis of novelty. MEXICA
  29. Social Physics Engines 29 Prom Week

  30. Social Physics Engines 30 Versu

  31. 31 Space Generation Systems

  32. Text-to-Image Systems 32

  33. 33 Skyrim Radiant Quests

  34. 34 GameForge: As seen in the PCG Book Story as

    input Valid space as output
  35. 35 Complete Story Generation Systems

  36. 36 Fabulist Initial State Revision Example: location of a hidden

    weapon needed for stealthy assassination
  37. 37 Generating space on the fly Virtual Storyteller: Late commitment

    Inspired by improvisational theater Example: Character want to fight each other? Spawn some weapons Similarly, Li and Riedl: Gadget generation
  38. 38 Scheherezade Crowd-sourced story choices

  39. 39 Universe Generating backstories for characters with family tree simulation

    Temporal coherence: if plot requires two characters to fall in love, their birthdates must be within a reasonable range of one another
  40. 40 Dwarf Fortress “Emergent Storytelling”

  41. 41 Classification Scheme

  42. Plot Automation 42 Manual Structure Template Constrained Automated

  43. Plot Automation 43 Structure Computer provides plot structure, but no

    specific events or event orderings. e.g. Scrivener
  44. Plot Automation 44 Template Computer provides plot template with events

    in order, but instantiation with existents is left to the human author. e.g. Propp grammars
  45. Plot Automation 45 Constrained Author provides initial state or other

    narrative constraints; computer gives complete plot populated with existents. e.g. GME, Mexica, Prom Week
  46. Space Automation 46 Manual Modification Simulation Constrained Automated

  47. Space Automation 47 Modification Author provides a starting point, but

    the computer can modify it, e.g. to suit the plot structure. e.g.: initial state revision; late commitment
  48. Space Automation 48 Simulation New spatial content is generated by

    simulating interactions between hand-authored existents, resulting in an initial state for story. e.g.: Universe’s family tree generation
  49. Space Automation 49 Constrained New spatial content is generated to

    satisfy authored constraints. e.g.: Dwarf Fortress
  50. 50

  51. 51

  52. 52 Examples to test classification

  53. 53

  54. Ice-Bound 54

  55. Epitaph 55