A Context-Integrated Transformer-Based Neural Network for Auction Design. (arXiv:2201.12489v2 [cs.GT] UPDATED)

Web: http://arxiv.org/abs/2201.12489

One of the central problems in auction design is developing an
incentive-compatible mechanism that maximizes the auctioneer's expected
revenue. While theoretical approaches have encountered bottlenecks in
multi-item auctions, recently, there has been much progress on finding the
optimal mechanism through deep learning. However, these works either focus on a
fixed set of bidders and items, or restrict the auction to be symmetric. In
this work, we overcome such limitations by factoring \emph{public} contextual
information of bidders and items into the …

arxiv context design network neural neural network transformer