Abstract
Traditional incentive-compatible auctions [6,16] for selling multiple goods to unconstrained and budgeted bidders can discriminate between bidders by selling identical goods at different prices. For this reason, Feldman et al. [7] dropped incentive compatibility and turned the attention to revenue maximizing envy-free item-pricing allocations for budgeted bidders. Envy-free allocations were suggested by classical papers [9,15]. The key property of such allocations is that no one envies the allocation and the price charged to anyone else. In this paper we consider this classical notion of envy-freeness and study fixed-price mechanisms which use nondiscriminatory uniform prices for all goods. Feldman et al. [7] gave an item-pricing mechanism that obtains 1/2 of the revenue obtained from any envy-free fixed-price mechanism for identical goods. We improve over this result by presenting an FPTAS for the problem that returns an (1 − ε)-approximation of the revenue obtained by any envy-free fixed-price mechanism for any ε > 0 and runs in polynomial time in the number of bidders n and 1/ ε even for exponential supply of goods m. Next, we consider the case of budgeted bidders with matching-type preferences on the set of goods, i.e., the valuation of each bidder for each item is either v i or 0. In this more general case, we prove that it is impossible to approximate the optimum revenue within O( min (n,m)1/2 − ε) for any ε > 0 unless P = NP. On the positive side, we are able to extend the FPTAS for identical goods to budgeted bidders in the case of constant number of different types of goods. Our FPTAS gives also a constant approximation with respect to the general envy-free auction.
This work was partially supported by Google Focused Award “Algorithms for Large-scale Data Analysis”, ERC StG project PAAl 259515, and FET IP project MULTIPEX 317532.
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Colini-Baldeschi, R., Leonardi, S., Sankowski, P., Zhang, Q. (2014). Revenue Maximizing Envy-Free Fixed-Price Auctions with Budgets. In: Liu, TY., Qi, Q., Ye, Y. (eds) Web and Internet Economics. WINE 2014. Lecture Notes in Computer Science, vol 8877. Springer, Cham. https://doi.org/10.1007/978-3-319-13129-0_18
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DOI: https://doi.org/10.1007/978-3-319-13129-0_18
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