Computational Social Choice: Strategic and Combinatorial Aspects

When agents have conflicting preferences over a set of alternatives and they want to make a joint decision, a natural way to do so is by voting. How to design and analyze desirable voting rules has been studied by economists for centuries. In recent decades, technological advances, especially those in internet economy, have introduced many new applications for voting theory. For example, we can rate movies based on people’s preferences, as done on many movie recommendation sites. However, in such new applications, we always encounter a large number of alternatives or an overwhelming amount of information, which makes computation in voting process a big challenge. Such challenges have led to a burgeoning area—computational social choice, aiming to address problems in computational aspects of preference representation and aggregation in a multi-agent scenario. The high-level goal of my research is to better understand and prevent the agents’ (strategic) behavior in voting systems, as well as to design computationally efficient ways for agents to present their preferences and make a joint decision.