Abstract
In this demonstration, we present an implementation of an emotion twenty questions (EMO20Q) questioner agent. The ubiquitous twenty questions game is a suitable format to study how people describe emotions and designing a computer agent to learn and reason about abstract emotion concepts can provide further theoretical insights. While natural language poses many challenges for the computer in human-computer interaction, the accessibility of natural language has made it possible to acquire data of many players reasoning about emotions in human-human games. These data are used to automate a computer questioner agent that asks the user questions and, based on that user's answers, attempts to guess the emotion that the user has in mind.