arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1401.2702cs.GT
收藏

通过Bundles清算市场

Clearing Markets via Bundles

Michal Feldman, Brendan Lucier

摘要:

我们研究组合市场设计问题的算法,其中一组异构和不可分割的对象的定价和出售给潜在的买家受到均衡约束。扩展了Feldman等人[STOC 2013]引入的CWE概念,我们引入了市场清算组合瓦尔拉斯均衡(MC-CWE)的概念,作为经典瓦尔拉斯均衡(WE)解决方案概念的自然放松。MC-CWE和WE之间的唯一区别是卖方在销售前捆绑商品的能力。这种无害和自然的捆绑操作带来了大量的算法和经济挑战和机遇。与WE不同的是,它保证只存在于(总)替代品估值中,MC-CWE总是存在的。因此,主要的算法挑战是设计计算效率高的机制,产生MC-CWE结果,近似最大化社会福利。对于各种估值类,包括替代品和补充(包括超添加剂,一心一意和非添加剂估值),我们设计多项式时间MC-CWE机制,提供紧密的福利近似结果。

英文摘要:

We study algorithms for combinatorial market design problems, where a set of heterogeneous and indivisible objects are priced and sold to potential buyers subject to equilibrium constraints. Extending the CWE notion introduced by Feldman et al. [STOC 2013], we introduce the concept of a Market-Clearing Combinatorial Walrasian Equilibium (MC-CWE) as a natural relaxation of the classical Walrasian equilibrium (WE) solution concept. The only difference between a MC-CWE and a WE is the ability for the seller to bundle the items prior to sale. This innocuous and natural bundling operation imposes a plethora of algorithmic and economic challenges and opportunities. Unlike WE, which is guaranteed to exist only for (gross) substitutes valuations, a MC-CWE always exists. The main algorithmic challenge, therefore, is to design computationally efficient mechanisms that generate MC-CWE outcomes that approximately maximize social welfare. For a variety of valuation classes encompassing substitutes and complements (including super-additive, single-minded and budget-additive valuations), we design polynomial-time MC-CWE mechanisms that provide tight welfare approximation results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑