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Auctioning a Cake: Truthful Auctions of Heterogeneous Divisible Goods

机译:拍卖蛋糕:异构可分离商品的真实拍卖

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We consider the problem of auctioning a one-dimensional continuously-divisible heterogeneous good (a.k.a. "the cake") among multiple agents. Applications include auctioning of time intervals, e.g. auctioning time for usage of a shared device, auctioning TV commercial slots, and more. Different agents may have different valuations for the different possible intervals, and the goal is to maximize the aggregate utility. Agents are self-interested and may misrepresent their true valuation functions, if this benefits them. Thus, we seek auctions that are truthful. Considering the case that each agent may obtain a single interval, the challenge is twofold, as we need to determine both where to slice the interval, and who gets which slice. The associated computational problem is NP-hard even under very restrictive assumptions. We consider two settings: discrete and continuous. In the discrete setting we are given a sequence of m indivisible elements (e_1,...,e_m), and the auction must allocate each agent a consecutive subsequence of the elements. For this setting we provide a truthful auctioning mechanism that approximates the optimal welfare to within a log m factor. The mechanism works for arbitrary monotone valuations. In the continuous setting we are given a continuous, infinitely divisible interval, and the auction must allocate each agent a sub-interval. The agents' valuations are non-atomic measures on the interval. For this setting we provide a truthful auctioning mechanism that approximates the optimal welfare to within a O(logn) factor (where n is the number of agents). Additionally, we provide a truthful 2-approximation mechanism for the case that all slices must be of some fixed size.
机译:我们考虑在多个药剂中拍卖一维连续可分地的异​​构良好(A.K.A.“蛋糕”)的问题。应用包括拍卖时间间隔,例如时间间隔。拍卖时间使用共享设备,拍卖电视商用插槽等。不同的代理可能对不同可能的间隔具有不同的估值,目标是最大化聚合实用程序。代理人是自我兴趣的,如果这有利于他们,可能会误解他们的真实估值职能。因此,我们寻求核心真实的。考虑到每个代理可以获得单个间隔的情况,挑战是双重的,因为我们需要确定切片的位置,谁得到哪个切片。即使在非常限制的假设下,相关的计算问题也是np-subly。我们考虑两个设置:离散和连续。在离散设置中,我们被给出了一系列M个不可类的元素(e_1,...,e_m),并且拍卖必须分配每个代理的元素的连续子序列。对于此设置,我们提供了一种真实的拍卖机制,使最佳福利近似于日志M因素。该机制适用于任意单调估值。在连续设置中,我们被赋予了连续的,无限的可分隔的间隔,并且拍卖必须将每个代理分配一个子间隔。代理商的估值是关于间隔的非原子措施。对于此设置,我们提供了一种真实的拍卖机制,使最佳福利近似于O(logn)因子(其中n是代理的数量)。此外,我们为所有切片必须具有一些固定大小的情况提供了真实的2近似机制。

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