Inferring individual behavioral tendencies in group interaction networks in socio-technical systems

Characterizing individual behavior in a group interaction context using Inverse Reinforcement Learning. A person in a work team and a county in an international group can both be considered as “individual in a group interaction context”. The method proposed and investigated in this project can be used to answer questions such as “what kind of teammate is this person?” or “what kind of behavior does Country A exhibit?”

Status of this project: completed, but collaborators welcome.

Publication: Wu, C. (2021). Connections between Relational Event Model and Inverse Reinforcement Learning for Characterizing Group Interaction Sequences. IEEE Transactions on Computational Social Systems.