Conference Papers

Learning about Human Personality

AuthorSebastian Ahrndt, Sahin Albayrak
Source15th German Conference on Multiagent System Technologies (MATES 2017) 

This work approaches the question whether or not agents are able to learn the personality of a human during interaction. We develop two agent-models to learn about the personality of humans during repeatedly played rounds in the Colored Trails Game. Human personality is described using a psychological theory of personality traits known as the Five-Factor Model. The results show that some characteristics of a personality can be learned more accurately and easily than others. The work extends the state-of-the-art in that it does not follow a supervised learning approach requiring existing data sets.