Towards Knowledge-Graph Constrained Generation for Text Adventure Games

Graham Todd, Zegang Cheng, Yifan Liu, Julian Togelius

TL;DR: We discuss a new potential kind of text adventure game, the difficulties in designing its underlying systems, and some avenues to explore for future research.

Abstract: Text adventure games provide players with a world to explore the opportunity to interact with it free from the constraints of typical games by using natural language to specify their actions. While revolutionary at the time, these games ultimately came with strict limits on the kinds of inputs they could successfully parse. Recent efforts have made use of large language models to create text adventure games capable of handling any input the user throws at it, but at the cost of lacking any sense of structure or permanence. Is it possible to combine the best aspects of both of these styles of text adventure games, resulting in a game that accepts broad user inputs while remaining grounded? We present one potential method for tackling this problem and discuss both the major difficulties and some potential avenues to explore.

Archival: Non-Archival