AI Faces the Ultimate Boss: Dungeons & Dragons

Research into understanding the capacity of Artificial Intelligence (AI) takes unexpected paths, such as using Dungeons & Dragons (D&D) as a sophisticated benchmark to evaluate how Large Language Models (LLMs) handle long-term, independent tasks.

While most AI research focuses on short-term prompts, D&D requires multi-step planning, strict adherence to complex rules, and collaborative strategy, providing a framework that scientists at the University of California, San Diego (UCSD) say is a “natural testing ground” for persistent AI agents.

The UCSD study utilises a game engine to enforce rules and provide maps, minimising AI “hallucinations”, instances when the LLMs produce fabrications.

AI agents played as heroes and monsters in combat scenarios, competing against each other and over 2 000 experienced human players. Researchers tracked the models’ ability to manage resources, choose tactical actions, and maintain a consistent “persona.”

“Our evaluation across six metrics reveals that [LLMs] produced a promising result in rule-based conversation simulation,” explained the study’s author, Raj Ammanabrolu. He went on to add: “Smaller, open-source language models, however, are not yet capable of giving consistent simulation, which might be because their pre-trained tuning is different compared to the D&D simulation task.”

Ultimately, the team found that all models suffered from progressive degradation during long-horizon scenarios, which remains a significant hurdle. The research team now plans to expand the simulation from isolated combat to full, narrative-driven campaigns further, to test the limits of AI’s long-term viability.