An Introduction to AI Story Generation

Automated story generation is the use of an intelligent system to produce a fictional story from a minimal set of inputs. This is a problem that has long been explored by AI researchers, since it strikes at some fundamental research questions in artificial intelligence. To tell a story, an intelligent system has to have a lot of knowledge, both about how to tell a story and about how the world works. These concepts need to be grounded to be able to tell coherent stories. Story generation is therefore an excellent way to know if an intelligent system truly understands something. To understand a concept, one must be able to put that concept into practice -- telling a story in which a concept is used correctly is one way of doing that. For example, if an AI system tells a story about going to a restaurant, as simple as that sounds, we discover very quickly what the system doesn't understand when it messes up basic details. Besides understanding concepts, storytelling also requires an understanding of the listener or reader, known as a theory of mind -- a model of the listener to reason about what needs to be said or what can be left out and still convey a comprehensible story. In addition to these fundamental AI research problems, automated story generation is also worth studying for the applications it may enable. The remainder of this article will present a primer on the field of research that I think my students need to know to get started on research on automated story generation, and that anyone interested in the topic of automated story generation may find it informative. A caveat: since I have been actively researching automated story generation for nearly two decades, this primer will be somewhat biased toward work from my research group and collaborators. We might distinguish between automated story generation and automated plot generation.