Abstract: We consider the problem of designing optimal mechanisms for settings where agents have dynamic private information. We present the Virtual-Pivot Mechanism, that is optimal in a large class of environments that satisfy a separability condition. The mechanism satisfies a rather strong equilibrium notion (it is periodic ex-post incentive compatible and individually rational). We provide both necessary and sufficient conditions for immediate incentive compatibility for mechanisms that satisfy periodic ex-post incentive compatibility in future periods. The result also yields a simple mechanism for selling a sequence of items to a single buyer. We also show the allocation rule of the Virtual-Pivot Mechanism has a very simple structure (a Virtual Index) in multi-armed bandit settings.
This is based on joint work with Sham Kakade and Ilan Lobel.
Hamid Nazerzadeh is an Assistant Professor in the Information and Operations Management Department at the Marshall School of Business, University of Southern California. He received his Ph.D. in Operations Research from Stanford University. His research interests include market design, revenue management, and optimization algorithms. Prior to joining the Marshall School, he was post-doc researcher at Microsoft Research, New England lab. He holds several patents on Internet advertising and cloud computing services.