2010/01/26 by Sham M. Kakade, Kakade, Sham M., Ilan Lobel +3
Decision Sciences · #Advanced Bandit Algorithms Research #Auction Theory and Applications #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Game Theory and Applications
paper · pdf · doi:10.48550/arxiv.1001.4598
openalex publication_date 2010/01/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We consider the problem of revenue-optimal dynamic mechanism design in settings where agents' types evolve over time as a function of their (both public and private) experience with items that are auctioned repeatedly over an infinite horizon. A central question here is understanding what natural restrictions on the environment permit the design of optimal mechanisms (note that even in the simpler static setting, optimal mechanisms are characterized only under certain restrictions). We provide a \em structural characterization of a natural "separable: multi-armed bandit environment (where the evolution and incentive structure of the a-priori type is decoupled from the subsequent experience in a precise sense) where dynamic optimal mechanism design is possible. Here, we present the Virtual Index Mechanism, an optimal dynamic mechanism, which maximizes the (long term) \em virtual surplus using the classical Gittins algorithm. The mechanism optimally balances exploration and exploitation, taking incentives into account.