Affine Maximizer Auction

Affine Maximizer Auctions (AMAs) are a class of auction mechanisms designed to maximize seller revenue while incentivizing truthful bidding from buyers (strategy-proofness). Current research focuses on improving the scalability of AMAs, particularly for combinatorial auctions with many items and bidders, often employing neural network architectures like AMenuNet and optimization techniques combining zeroth- and first-order methods to learn optimal AMA parameters. This work is significant because it addresses the inherent computational challenges in designing and implementing strategy-proof auctions, leading to more efficient and fair allocation of resources in various applications, such as online advertising and resource management.