The National Science Foundation Division of Information and Intelligent Systems awarded a $154,231 Project Grant to the University of Texas at Austin under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The two-year award will support research to develop a generative deep learning framework for approximating human decision-making processes on social networks when structural network data is unavailable. Specifically, the university researchers will analyze the fundamental identifiability of learning network structures from observed decisions. They will also extend prior work on linear-quadratic network games to broader classes of games. Finally, the team will apply their theoretical findings to network intervention design and privacy risk evaluation using large behavioral data sets and experimental data. The work builds on fields including game theory, machine learning, network science, and management science.
Generated 1/6/24, 5:02 PM