Multi-item auctions defying intuition?
C Daskalakis - ACM SIGecom Exchanges, 2015 - dl.acm.org
ACM SIGecom Exchanges, 2015•dl.acm.org
The best way to sell n items to a buyer who values each of them independently and
uniformly randomly in [c, c+ 1] is to bundle them together, as long as c is large enough. Still,
for any c, the grand bundling mechanism is never optimal for large enough n, despite the
sharp concentration of the buyer's total value for the items as n grows. Optimal multi-item
mechanisms are rife with unintuitive properties, making multi-item generalizations of
Myerson's celebrated mechanism a daunting task. We survey recent work on the structure …
uniformly randomly in [c, c+ 1] is to bundle them together, as long as c is large enough. Still,
for any c, the grand bundling mechanism is never optimal for large enough n, despite the
sharp concentration of the buyer's total value for the items as n grows. Optimal multi-item
mechanisms are rife with unintuitive properties, making multi-item generalizations of
Myerson's celebrated mechanism a daunting task. We survey recent work on the structure …
The best way to sell n items to a buyer who values each of them independently and uniformly randomly in [c, c+1] is to bundle them together, as long as c is large enough. Still, for any c, the grand bundling mechanism is never optimal for large enough n, despite the sharp concentration of the buyer's total value for the items as n grows. Optimal multi-item mechanisms are rife with unintuitive properties, making multi-item generalizations of Myerson's celebrated mechanism a daunting task. We survey recent work on the structure and computational complexity of revenue-optimal multi-item mechanisms, providing structural as well as algorithmic generalizations of Myerson's result to multi-item settings.