Situated language learning via interactive narratives

Prithviraj Ammanabrolu, Mark O. Riedl

Abstract: This paper provides a roadmap that explores the question of how to imbue learning agents with the ability to understand and generate contextually relevant natural language in service of achieving a goal. We hypothesize that two key components in creating such agents are interactivity and environment grounding, shown to be vital parts of language learning in humans, and posit that interactive narratives should be the environments of choice for such training these agents. These games are simulations in which an agent interacts with the world through natural language—perceiving, acting upon, and talking to the world using textual descriptions, commands, and dialogue—and, as such, exist at the intersection of natural language processing, storytelling, and sequential decision making.