Using Language Models to Convert Between Natural Language and Game Commands

Stefan Papazov, Wesley Gill, Marta Garcia Ferreiro, Andrew Zhu, Lara J. Martin, Chris Callison-Burch

Keywords: command translation, story generation, dungeons and dragons

TL;DR: We use GPT-3 translate between natural language and D&D game commands with few shot learning and fine tuning.

Abstract: Dungeons and Dragons is a popular tabletop role-playing game that has been adapted to online play. In this paper, we look at enhancing a Discord Bot called Avrae that is developed by D&D Beyond to help with online play. Avrae enables users to manage gameplay through Unix-like commands. We explore using language models to automatically translate player dialogue into Avrae's commands. We use GPT-3's few shot learning and fine tuning capabilities and achieve 64% accuracy. We also explore the reverse direction, where commands are rendered as descriptive text, suggesting that it may eventually be possible to combine Avrae and LMs to create a system that is capable of role-playing alongside players.

Archival: Non-Archival