I originally posted this on /r/learnmachinelearning since it’s technically a question, but I think it goes beyond the scope of questions like “how do I set up tensorflow” and is worth putting here well.

I love tabletop RPGs, and I’m specifically curious if there are any areas of current ML technology that might allow the nerd fantasy of an independent AI dungeon master to come true, whether fully or even partially.

For those unfamiliar with tabletop RPGs, I’ll run over the basic gameplay loop, using Dungeons & Dragons as my example.

At the center of it all you have a system of core rules (easily programmable rules, in fact) which tracks character stats, specifics of movement, items, abilities, success/failure checks, and other details down to a very granular level. This part is easy for computers, evidenced by the fact that RPG video games derived from these rulesets.

However, with a tabletop RPG, the game is ran by a person known as the Dungeon Master or Game Master, who acts as a kind of referee for the rules. The Dungeon Master can take whatever request a player makes, then translate that request into something compatible with the rules.

This process of “compiling” a request into a rule check can be done for something simple, such as “I attack the orc” (damage based on a dice roll + weapon type + skill modifiers + proficiency bonus, etc.), or for something crazy and convoluted, such as “I fashion the rope in my inventory into a lasso and toss it so that it loops around the damaged stone pillar at the other side of the chasm” (dice roll based on the player’s dexterity skill), followed by “I pull the rope as hard as I can” (another roll based on their strength skill, success resulting in the pillar toppling and creating a bridge of rubble, and the player losing the rope item) followed by “I walk across the rubble to cross” (dice roll based on the player’s acrobatics ability to update the player’s position and allow them to continue the loop by interacting with things on the other side of the chasm).

So there is consistency mixed with inconsistency. A player’s input can be wild and unpredictable, but it always resolves into rule checks that are consistent, mechanical, and easily understandable by a machine. The Dungeon Master is the missing link. The adjudication of a human brain allows players to interact with the rules in a way that’s deeper and freer than clicking pre-programmed buttons to perform actions, which is why video games have never been able to replicate the feeling of a real tabletop RPG.

But now we have machine learning. What kind of AI, if any, could be used to taking ambiguous statements and convert them into standard game interactions? And to what extent could it be pushed? If it’s impossible to account for everything (which I’m guessing it is, at least for now), then what kind of sacrifices could be made on the player’s side (e.g. typing only short, simple requests in a specific format, or entering nouns and verbs into text boxes) to make it possible?