PhD Proposal: Computational Analysis of Intelligent Agents: Social and Strategic Settings

The goal of this study is to analyze and predict the behavior of multiple interacting intelligent agents. We propose and analyze theoretical models for behavior of such agents in social and strategic agents.
In social networks, we generalize and get new theoretical results for scheduling a cascade in a networks and for seed set selection for influence maximization. In strategic games, we study and develop new solution concept for the case when there is considerable uncertainties in payoffs. In addition, we apply our framework for analysis of a real-world strategic game involving five players.
Game theory for strategic games makes many assumptions. Specifically, it almost always assumes that payoffs are given. However, with increased availability of data, it should now be possible to mine human incentives from data. To achieve this we will develop a new data analytic framework for finding payoffs for a game.
Examining Committee:
Committee Co-Chairs: - Dr. V.S. Subrahmanian and Dr. Mohammad T.
Hajiaghayi
Dept's Representative - Dr. Amol Deshpande
Committee Member(s): - Dr. Dana Nau