Automated Storytelling via Causal, Commonsense Plot Ordering

Authors

  • Prithviraj Ammanabrolu Georgia Institute of Technology
  • Wesley Cheung Georgia Institute of Technology
  • William Broniec Georgia Institute of Technology
  • Mark O. Riedl Georgia Institute of Technology

Keywords:

Game Design -- Procedural Content Generation & Storytelling, Generation

Abstract

Automated story plot generation is the task of generating a coherent sequence of plot events. Causal relations between plot events are believed to increase the perception of story and plot coherence. In this work, we introduce the concept of soft causal relations as causal relations inferred from commonsense reasoning. We demonstrate C2PO, an approach to narrative generation that operationalizes this concept through Causal, Commonsense Plot Ordering. Using human-participant protocols, we evaluate our system against baseline systems with different commonsense reasoning reasoning and inductive biases to determine the role of soft causal relations in perceived story quality. Through these studies we also probe the interplay of how changes in commonsense norms across storytelling genres affect perceptions of story quality.

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Published

2021-05-18

How to Cite

Ammanabrolu, P., Cheung, W., Broniec, W., & Riedl, M. O. (2021). Automated Storytelling via Causal, Commonsense Plot Ordering. Proceedings of the AAAI Conference on Artificial Intelligence, 35(7), 5859-5867. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16733

Issue

Section

AAAI Technical Track on Humans and AI