How Players Speak to an Intelligent Game Character Using Natural Language Messages

Abstract

AI-driven characters that learn directly from human input are rare in digital games, but recent advances in several fields of machine learning suggests that they may soon be much more feasible to create. This study explores the design space for interacting with such a character through natural language text dialogue. We conducted an observational study with 18 high school students, who played Minecraft alongside a Wizard of Oz prototype of a companion AI character that learned from their actions and inputs. In this paper, we report on an analysis of the 186 natural language messages that players sent to the character, and review key variations in syntax, function and writing style. We find that players’ behaviour and language was differentiated by the extent to which they expressed an anthropomorphic view of the AI character and the level of interest that they showed in interacting with it.