English

Incentive Compatible Budget Elicitation in Multi-unit Auctions

Computer Science and Game Theory 2009-04-23 v1 Multiagent Systems

Abstract

In this paper, we consider the problem of designing incentive compatible auctions for multiple (homogeneous) units of a good, when bidders have private valuations and private budget constraints. When only the valuations are private and the budgets are public, Dobzinski {\em et al} show that the {\em adaptive clinching} auction is the unique incentive-compatible auction achieving Pareto-optimality. They further show thatthere is no deterministic Pareto-optimal auction with private budgets. Our main contribution is to show the following Budget Monotonicity property of this auction: When there is only one infinitely divisible good, a bidder cannot improve her utility by reporting a budget smaller than the truth. This implies that a randomized modification to the adaptive clinching auction is incentive compatible and Pareto-optimal with private budgets. The Budget Monotonicity property also implies other improved results in this context. For revenue maximization, the same auction improves the best-known competitive ratio due to Abrams by a factor of 4, and asymptotically approaches the performance of the optimal single-price auction. Finally, we consider the problem of revenue maximization (or social welfare) in a Bayesian setting. We allow the bidders have public size constraints (on the amount of good they are willing to buy) in addition to private budget constraints. We show a simple poly-time computable 5.83-approximation to the optimal Bayesian incentive compatible mechanism, that is implementable in dominant strategies. Our technique again crucially needs the ability to prevent bidders from over-reporting budgets via randomization.

Keywords

Cite

@article{arxiv.0904.3501,
  title  = {Incentive Compatible Budget Elicitation in Multi-unit Auctions},
  author = {Sayan Bhattacharya and Vincent Conitzer and Kamesh Munagala and Lirong Xia},
  journal= {arXiv preprint arXiv:0904.3501},
  year   = {2009}
}
R2 v1 2026-06-21T12:54:04.751Z