Using Language Models to Convert Between Natural Language and Game Commands

Files

10_using_language_models_to_conve.pdf (544.34 KB)

Links to Files

https://openreview.net/forum?id=jQSStHwtmDN

Permanent Link

http://hdl.handle.net/11603/31771

Collections

UMBC Computer Science and Electrical Engineering Department

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0002-0623-599X

Date

2022-07-05

Type of Work

journal articles
preprints
Text

Department

Program

Citation of Original Publication

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

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.