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Title: Open-World Narrative Generation to Answer Players’ Questions
Planning-based narrative generation is effective at producing stories with a logically-sound flow of events, but it can be limiting due to the rigidity of its constraints and the high burden on the domain author to define story-world objects, initial states, and author and character goals. Giving the system the freedom to add objects and events to the story-world history arbitrarily can improve variety and reduce authorial burden, but risks leading to stories that seem jarringly contrived to the audience. I propose to use question-answering as the antidote to contrivance in a highly-generative interactive narrative system: By modeling the player's beliefs about the story world, inferring the implicit questions the player may be asking through their interactions, and answering those questions in a way consistent with the player's prior knowledge, a system could focus on creating cohesion in the ways that matter most to the player while accepting a degree of contrivance in the details that the player is likely to overlook.  more » « less
Award ID(s):
1911053 2145153
Author(s) / Creator(s):
Date Published:
Journal Name:
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Page Range / eLocation ID:
307 to 310
Medium: X
Sponsoring Org:
National Science Foundation
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