We propose a novel task, G4C, to study teacher-student natural language interactions in a goal-driven and grounded environment. Dungeons and Dragons (D&D), a role-playing game, provides an ideal setting to investigate such interactions. Here, the Dungeon Master (DM), i.e., the teacher, guides the actions of several players -- students, each with their own personas and abilities -- to achieve shared goals grounded in a fantasy world. Our approach is to decompose and model these interactions into (1) the DM's intent to guide players toward a given goal; (2) the DM's guidance utterance to the players expressing this intent; and (3) a theory-of-mind (ToM) model that anticipates the players' reaction to the guidance one turn into the future. We develop a novel reinforcement learning (RL) method for training a DM that generates guidance for players by rewarding utterances where the intent matches the ToM-anticipated player actions. Human and automated evaluations show that a DM trained to explicitly model intents and incorporate ToM of the players using RL generates better-quality guidance that is 3x more likely to fulfill the DM's intent than a vanilla natural language generation (NLG) approach.

AI researchers have posited Dungeons and Dragons (D&D) as a challenge problem to test systems on various language-related capabilities. In this paper, we frame D&D specifically as a dialogue system challenge, where the tasks are to both generate the next conversational turn in the game and predict the state of the game given the dialogue history. We create a gameplay dataset consisting of nearly 900 games, with a total of 7,000 players, 800,000 dialogue turns, 500,000 dice rolls, and 58 million words. We automatically annotate the data with partial state information about the game play. We train a large language model (LM) to generate the next game turn, conditioning it on different information. The LM can respond as a particular character or as the player who runs the game--i.e., the Dungeon Master (DM). It is trained to produce dialogue that is either in-character (roleplaying in the fictional world) or out-of-character (discussing rules or strategy). We perform a human evaluation to determine what factors make the generated output plausible and interesting. We further perform an automatic evaluation to determine how well the model can predict the game state given the history and examine how well tracking the game state improves its ability to produce plausible conversational output.

Artificial intelligence has mastered even extremely complex games like chess and Go. However, these games have pre-defined rules and very specific methods of interaction that don't lend themselves to creative choices. A role-playing game like Dungeons and Dragons (DnD) has infinitely more ways to play than a game of chess does, but this hasn't stopped researchers from trying to develop AI systems capable of improvising storylines for DnD or similar tabletop role-playing games. AI researchers are constantly working on new ways to improve the generative language abilities of AI. One of the biggest advances in the past couple of years is the development GPT-2, which was able to generate coherent stories on the fly.

Artificial intelligence has mastered even extremely complex games like chess and Go. However, these games have pre-defined rules and very specific methods of interaction that don't lend themselves to creative choices. A role-playing game like Dungeons and Dragons (DnD) has infinitely more ways to play than a game of chess does, but this hasn't stopped researchers from trying to develop AI systems capable of improvising storylines for DnD or similar tabletop role-playing games. AI researchers are constantly working on new ways to improve the generative language abilities of AI. One of the biggest advances in the past couple of years is the development GPT-2, which was able to generate coherent stories on the fly.

In late November, a college senior at Brigham Young University named Nick Walton published a short fable called "My Musical Troupe of Orcs Uses Music to Advance Orc Rights." In the story, written in the second person, you are a goblin. "I am a goblin!" you say proudly. "And I'm glad to be one." "Well then, congratulations," says the orc captain. Over the course of a few hundred words, some big things happen: You ask if you can join the orc band.

On the 62nd floor of One World Trade Center, Lorghoth the Decayer is waiting. A party of brave coders and digital strategists gathers around a conference table to slay the wicked beast -- praying the D20 rolls their way. Every other week, a team of developers and designers hops into a conference room (with a stunning view of Manhattan) to participate in a unique, after-hours exercise: a Dungeons and Dragons game night. Timm Woods, a professional dungeon master, leads each session, guiding the colleagues through intricate adventures filled with gypsy-camp raids, vindictive scarecrows and the cruel mists of Ravenloft. Woods, an energetic and scruffy Brooklynite, has been a professional dungeon master for about five years, running everything from after-school campaigns to private parties and events.

Everyone had died--not that you'd know it, from how they were laughing about their poor choices and bad rolls of the dice. As a social anthropologist, I study how people understand artificial intelligence (AI) and our efforts towards attaining it; I'm also a life-long fan of Dungeons and Dragons (D&D), the inventive fantasy roleplaying game. During a recent quest, when I was playing an elf ranger, the trainee paladin (or holy knight) acted according to his noble character, and announced our presence at the mouth of a dragon's lair. But while success in D&D means "beating the bad guy," the game is also a creative sandbox, where failure can count as collective triumph so long as you tell a great tale. What does this have to do with AI?

Everyone had died – not that you'd know it, from how they were laughing about their poor choices and bad rolls of the dice. As a social anthropologist, I study how people understand artificial intelligence (AI) and our efforts towards attaining it; I'm also a life-long fan of Dungeons and Dragons (D&D), the inventive fantasy roleplaying game. During a recent quest, when I was playing an elf ranger, the trainee paladin (or holy knight) acted according to his noble character, and announced our presence at the mouth of a dragon's lair. But while success in D&D means'beating the bad guy', the game is also a creative sandbox, where failure can count as collective triumph so long as you tell a great tale. What does this have to do with AI?