3,771 research outputs found

    Weak Cartels and Collusion-Proof Auctions

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    We study private value auctions in which bidders may collude without using sidepayments. In our model, bidders coordinate their actions to achieve an outcome that interim-Pareto dominates the noncooperative outcome. We characterize auctions that are collusion-proof in the sense that no such coordination opportunities exist, and show that the efficient and revenue maximizing auctions are not collusion-proof unless all bidders exhibit a concave distribution of valuations. We then solve for revenue maximizing collusion-proof auctions. If distributions of valuations are symmetric and single-peaked, the optimal selling mechanism is a standard auction with a minimum bid, followed by sequential negotiation in case no bidder bids above the minimum bid

    Auctions with Severely Bounded Communication

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    We study auctions with severe bounds on the communication allowed: each bidder may only transmit t bits of information to the auctioneer. We consider both welfare- and profit-maximizing auctions under this communication restriction. For both measures, we determine the optimal auction and show that the loss incurred relative to unconstrained auctions is mild. We prove non-surprising properties of these kinds of auctions, e.g., that in optimal mechanisms bidders simply report the interval in which their valuation lies in, as well as some surprising properties, e.g., that asymmetric auctions are better than symmetric ones and that multi-round auctions reduce the communication complexity only by a linear factor

    Budget Constrained Auctions with Heterogeneous Items

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    In this paper, we present the first approximation algorithms for the problem of designing revenue optimal Bayesian incentive compatible auctions when there are multiple (heterogeneous) items and when bidders can have arbitrary demand and budget constraints. Our mechanisms are surprisingly simple: We show that a sequential all-pay mechanism is a 4 approximation to the revenue of the optimal ex-interim truthful mechanism with discrete correlated type space for each bidder. We also show that a sequential posted price mechanism is a O(1) approximation to the revenue of the optimal ex-post truthful mechanism when the type space of each bidder is a product distribution that satisfies the standard hazard rate condition. We further show a logarithmic approximation when the hazard rate condition is removed, and complete the picture by showing that achieving a sub-logarithmic approximation, even for regular distributions and one bidder, requires pricing bundles of items. Our results are based on formulating novel LP relaxations for these problems, and developing generic rounding schemes from first principles. We believe this approach will be useful in other Bayesian mechanism design contexts.Comment: Final version accepted to STOC '10. Incorporates significant reviewer comment

    Dynamic Auctions: A Survey

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    We survey the recent literature on designing auctions and mechanisms for dynamic settings. Two settings are considered: those with a dynamic population of agents or buyers whose private information remains fixed throughout time; and those with a fixed population of agents or buyers whose private information changes across time. Within each of these settings, we discuss both efficient (welfare-maximizing) and optimal (revenue-maximizing) mechanisms.Dynamic auctions and mechanisms, Random arrivals and departures, Changing private information, Incentive compatibility

    Dynamic threshold policy for delaying and breaking commitments in transportation auctions

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    In this paper we consider a transportation procurement auction consisting of shippers and carriers. Shippers offer time sensitive pickup and delivery jobs and carriers bid on these jobs. We focus on revenue maximizing strategies for shippers in sequential auctions. For this purpose we propose two strategies, namely delaying and breaking commitments. The idea of delaying commitments is that a shipper will not agree with the best bid whenever it is above a certain reserve price. The idea of breaking commitments is that the shipper allows the carriers to break commitments against certain penalties. The benefits of both strategies are evaluated with simulation. In addition we provide insight in the distribution of the lowest bid, which is estimated by the shippers

    On Revenue Monotonicity in Combinatorial Auctions

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    Along with substantial progress made recently in designing near-optimal mechanisms for multi-item auctions, interesting structural questions have also been raised and studied. In particular, is it true that the seller can always extract more revenue from a market where the buyers value the items higher than another market? In this paper we obtain such a revenue monotonicity result in a general setting. Precisely, consider the revenue-maximizing combinatorial auction for mm items and nn buyers in the Bayesian setting, specified by a valuation function vv and a set FF of nmnm independent item-type distributions. Let REV(v,F)REV(v, F) denote the maximum revenue achievable under FF by any incentive compatible mechanism. Intuitively, one would expect that REV(v,G)REV(v,F)REV(v, G)\geq REV(v, F) if distribution GG stochastically dominates FF. Surprisingly, Hart and Reny (2012) showed that this is not always true even for the simple case when vv is additive. A natural question arises: Are these deviations contained within bounds? To what extent may the monotonicity intuition still be valid? We present an {approximate monotonicity} theorem for the class of fractionally subadditive (XOS) valuation functions vv, showing that REV(v,G)cREV(v,F)REV(v, G)\geq c\,REV(v, F) if GG stochastically dominates FF under vv where c>0c>0 is a universal constant. Previously, approximate monotonicity was known only for the case n=1n=1: Babaioff et al. (2014) for the class of additive valuations, and Rubinstein and Weinberg (2015) for all subaddtive valuation functions.Comment: 10 page
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