# Strategic Bidding in Knapsack Auctions

arXiv: https://arxiv.org/abs/2403.07928 · HTML: https://mlsanity.com/paper/2403.07928/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Mar 2024.

## Built on by (most cited first, 1 of 1)

- [Artificial Intelligence for Multi-Unit Auction design](https://mlsanity.com/paper/2404.15633/) (2024)

## Abstract (arXiv)

This paper examines knapsack auctions as a method to solve the knapsack problem with incomplete information, where object values are private and sizes are public. We analyze three auction types-uniform price (UP), discriminatory price (DP), and generalized second price (GSP)-to determine efficient resource allocation in these settings. Using a Greedy algorithm for allocating objects, we analyze bidding behavior, revenue and efficiency of these three auctions using theory, lab experiments, and AI-enriched simulations. Our results suggest that the uniform-price auction has the highest level of truthful bidding and efficiency while the discriminatory price and the generalized second-price auctions are superior in terms of revenue generation. This study not only deepens the understanding of auction-based approaches to NP-hard problems but also provides practical insights for market design.