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. However, as Wired reported, Georgia Tech graduate student Lara Martin conceived of using DnD as a test case for an AI’s generative language ability. The goal is essentially to create an AI dungeon-master, capable of creating new scenarios for the game and adapting these scenarios.
According to Wired, Martin has been working on the AI dungeon master since 2018. Language generation models often use either rules-based approaches or neural networks based approaches. Recently, there has been an increasing interest in combining the two techniques to generate language. Martin’s approach utilizes rules-based language generation strategies alongside deep neural networks. Martin’s approach to language generation relies on the idea of “events”. Events consist of various parts of speech like objects, subjects, and verbs, which the model combines into event objects that are coherent. The model was trained on storylines from popular sci-fi Tv shows like Futurama and Doctor Who. The model is primed with a string of text, which it will analyze for events. After extracting the events from the priming text, it will attempt to continue the plot by generating new events. Martin was able to expand on this basic approach and guide the model towards generating certain desired events, like the marriage of two characters within the story.
Martin isn’t the only researcher attempting to design AI’s capable of telling stories. For example, machine learning researcher Nick Walton recently developed AI Dungeon, which makes use of GPT-2 models to create an AI-generated text-adventure game. While AI Dungeon typically renders text that is at least coherent, it tends to lose track of the overall narrative, start strange new plot threads, and generally behave oddly to player input. Despite these limitations, the game has proved rather popular, with over a million people playing it.
Martin acknowledges the limits of the model, stating that the model often gets confused, generating plot events that don’t make logical sense, and that “we’re nowhere close to this being a reality yet”. Despite this, Martin still hopes that the model will lead to something useful in the future. Martin is also hopeful that the project could potentially give us insight into how the creation of stories leverages different aspects of intelligence like imagination and embodiment.
“If we could create a convincing AI DM, it would tell us more about how we create and experience these worlds,” Martin explained to Wired.
It could also be argued that the challenge of accomplishing a feat as difficult as creating a dungeon master AI is reason enough to pursue the project. Noah Smith, an AI and language professor at the University of Washington explained that large goals sometimes help create usable applications, even if the challenge itself isn’t accomplished in a timely fashion.
“Sometimes grand challenge goals are helpful in getting a lot of researchers moving in a single direction. And some of what spins out is also useful in more practical applications.”
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