Predictability in human-agent cooperation: adapting to humans' personalities

Making artificial agents a constituent part of human activities leads to more affiliated teamwork scenarios and at the same time introduces several new challenges. One challenge is the team members’ ability to be mutually predictable, which is required to effectively plan own actions, e.g., in the field of human-aware planning. This work approaches the question whether or not agents are able to learn the personality of a human during interaction. In particular, we developed an agent model able to learn human personality during repeatedly played rounds in the Colored Trails Game. Human personality is described using a psychological theory of personality types known as the Five-Factor Model. The results indicate that some characteristics of a personality can be learned more accurately/easily than others. Categories and Subject Descriptors I.2 [Artificial Intelligence]: Learning; J.4 [Computer Applications]: Social and Behavioural Sciences Keywords Information systems, User/Machine...

• Type: Journal
• Year: 2015
• Where: SAC
• Authors: Sebastian Ahrndt, Benjamin Breitung, Johannes Fähndrich, Sahin Albayrak
• Keywords: Applied Computing, SAC 2015