Controllable Neural Story Plot Generation via Reward Shaping

Controllable Neural Story Plot Generation via Reward Shaping

Pradyumna Tambwekar, Murtaza Dhuliawala, Lara J. Martin, Animesh Mehta, Brent Harrison, Mark O. Riedl

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
AI for Improving Human Well-being. Pages 5982-5988. https://doi.org/10.24963/ijcai.2019/829

Language-modeling--based approaches to story plot generation attempt to construct a plot by sampling from a language model (LM) to predict the next character, word, or sentence to add to the story. LM techniques lack the ability to receive guidance from the user to achieve a specific goal, resulting in stories that don't have a clear sense of progression and lack coherence. We present a reward-shaping technique that analyzes a story corpus and produces intermediate rewards that are backpropagated into a pre-trained LM in order to guide the model toward a given goal. Automated evaluations show our technique can create a model that generates story plots which consistently achieve a specified goal. Human-subject studies show that the generated stories have more plausible event ordering than baseline plot generation techniques.
Keywords:
Special Track on AI for Improving Human-Well Being: Entertainment;games applications (Special Track on AI and Human Wellbeing)