组合域上的成本分担

IF 1.1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ACM Transactions on Economics and Computation Pub Date : 2022-03-31 DOI:10.1145/3505586
Georgios Birmpas, E. Markakis, G. Schäfer
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引用次数: 0

摘要

研究组合领域的成本分担机制设计问题。假设有多个项目或服务可以在一组感兴趣的代理之间共享。在此设置中,机制的结果包括分配,确定每个道具的玩家组,以及各自的支付。虽然有一些研究此类问题的专门版本的工作,但直到最近才在一般组合成本分担领域取得进展。尽管如此,关于战略可靠性、成本回收和经济效率之间相互作用的许多问题仍未得到解答。我们工作的主要目标是进一步了解预算平衡和社会成本近似方面的这种相互作用。为此,我们提供了适用于迭代机制的交叉单调性(我们称之为跟踪单调性)的改进。这里的跟踪指的是玩家最终完成的顺序。在此之上,我们还提供了成本函数的两个参数化(在一定程度上是互补的),它们捕获了它们的平均成本份额的行为。基于我们的跟踪单调性,我们设计了一种迭代上升的成本分担机制,该机制适用于具有对称次模值的组合成本分担设置。使用我们的第一个成本函数参数化,我们确定了我们的机制是弱群体策略证明,\( O(1) \) -预算平衡和\( O(H_n) \) -近似于社会成本的条件。进一步,我们证明了我们的机制是预算平衡和\( H_n \) -近似的,如果估值和成本函数都是对称的子模;考虑到现有的不可能结果,这是最好的可能。最后,我们考虑了一般的估值函数,并利用我们的第二个参数化来推导出由Moulin引入的序列机制的更细粒度的分析。这种机制通过建设实现预算平衡,但一般来说,只能保证一个糟糕的社会成本近似\( n \)。我们确定了该机制实现改进的社会成本近似保证的条件。特别是,我们推导了改进的机制来解决基本的成本分摊问题,包括顶点覆盖和集合覆盖。
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Cost Sharing over Combinatorial Domains
We study the problem of designing cost-sharing mechanisms for combinatorial domains. Suppose that multiple items or services are available to be shared among a set of interested agents. The outcome of a mechanism in this setting consists of an assignment, determining for each item the set of players who are granted service, together with respective payments. Although there are several works studying specialized versions of such problems, there has been almost no progress for general combinatorial cost-sharing domains until recently [9]. Still, many questions about the interplay between strategyproofness, cost recovery, and economic efficiency remain unanswered. The main goal of our work is to further understand this interplay in terms of budget balance and social cost approximation. Towards this, we provide a refinement of cross-monotonicity (which we term trace-monotonicity) that is applicable to iterative mechanisms. The trace here refers to the order in which players become finalized. On top of this, we also provide two parameterizations (complementary to a certain extent) of cost functions, which capture the behavior of their average cost-shares. Based on our trace-monotonicity property, we design an Iterative Ascending Cost-Sharing Mechanism, which is applicable to the combinatorial cost-sharing setting with symmetric submodular valuations. Using our first cost function parameterization, we identify conditions under which our mechanism is weakly group-strategyproof, \( O(1) \) -budget-balanced, and \( O(H_n) \) -approximate with respect to the social cost. Furthermore, we show that our mechanism is budget-balanced and \( H_n \) -approximate if both the valuations and the cost functions are symmetric submodular; given existing impossibility results, this is best possible. Finally, we consider general valuation functions and exploit our second parameterization to derive a more fine-grained analysis of the Sequential Mechanism introduced by Moulin. This mechanism is budget balanced by construction, but in general, only guarantees a poor social cost approximation of \( n \) . We identify conditions under which the mechanism achieves improved social cost approximation guarantees. In particular, we derive improved mechanisms for fundamental cost-sharing problems, including Vertex Cover and Set Cover.
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来源期刊
ACM Transactions on Economics and Computation
ACM Transactions on Economics and Computation COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
3.80
自引率
0.00%
发文量
11
期刊介绍: The ACM Transactions on Economics and Computation welcomes submissions of the highest quality that concern the intersection of computer science and economics. Of interest to the journal is any topic relevant to both economists and computer scientists, including but not limited to the following: Agents in networks Algorithmic game theory Computation of equilibria Computational social choice Cost of strategic behavior and cost of decentralization ("price of anarchy") Design and analysis of electronic markets Economics of computational advertising Electronic commerce Learning in games and markets Mechanism design Paid search auctions Privacy Recommendation / reputation / trust systems Systems resilient against malicious agents.
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