The modern economy is becoming highly digital, demanding a combination of both economic and computational techniques. The abundance of data and the unique nature of digital markets highlight the special role of information in today’s economic systems. In this talk, I will discuss two domains of interest. The first is auction design in the interdependent value (IDV) setting. In IDV settings, buyers hold partial information regarding the quality of the good being sold, but their actual values also depend on information that other buyers have about the good. The second is indirect mechanism design, in which the economic system can only observe partial information regarding the buyers’ preferences, if any. In both domains, impossibilities are known for very basic settings. I will show how my research has pushed the boundary of what is possible via a computational approach. For IDV settings, I utilize techniques from approximation algorithms to obtain the first general positive results for combinatorial auctions. For indirect mechanisms, I initiate the use of reinforcement learning for the design of such mechanisms.
Alon Eden is a postdoctoral fellow at Harvard School of Engineering and Applied Sciences. His main research interests lie in the interface of computer science and economics, where he applies computational tools in the design and analysis of economic mechanisms. He is interested in the role of information in modern market settings, such as extracting information dispersed among bidders in an auction setting and using machine learning tools to study auction design.
Alon completed his PhD in computer science from Tel Aviv University under the supervision of Prof. Michal Feldman and Prof. Amos Fiat. He was awarded the Michael B. Maschler Prize of the Israeli Chapter of the Game Theory Society for the best PhD thesis of 2019. He was also awarded Best Paper at SAGT’17 and Best Paper with Lead Student Author at EC’19. He received an honorable mention for the Best Presentation by a Student or Postdoctoral Researcher award at EC’19.