论文标题

对串行独裁统治的优化

Optimizing over Serial Dictatorships

论文作者

Caragiannis, Ioannis, Rathi, Nidhi

论文摘要

由串行独裁机制在社会选择环境中的成功的动机,我们探索了它在解决各种组合优化问题方面的有用性。我们通过考虑一个抽象模型来做到这一点,其中要求一组代理以特定的顺序作用,称为动作序列。鉴于在动作序列之前的代理人的行为,每个代理都以给她最大可能的价值的方式行事。我们的目标是计算为代理人(又称社会福利)产生大约最佳总价值的动作序列。我们假设查询对代理在订购的代理商以$ s $ s $之后行动时获得的值$ v_i(s)$的查询访问权限。 我们建立了有关社会福利的紧密界限,可以使用多个疑问可以实现的社会福利。即使这些界限通常显示出最佳社会福利的略有额定性近似,但当估值源于基础组合域时,也可以获得出色的近似值。有指示的是,当使用二分匹配,有向图中的轴心以及布尔表达式满意度定义估值时,简单的查询效率算法产生$ 2 $ - APPRXIMATIONS。我们讨论与真实性有关的问题,并展示如何使用类似VCG的付款真实地实现我们的某些算法。最后,我们介绍和研究串行独裁统治的价格,该概念对由动作序列产生的组合优化解决方案的质量进行了乐观的衡量。

Motivated by the success of the serial dictatorship mechanism in social choice settings, we explore its usefulness in tackling various combinatorial optimization problems. We do so by considering an abstract model, in which a set of agents are asked to act in a particular ordering, called the action sequence. Each agent acts in a way that gives her the maximum possible value, given the actions of the agents who preceded her in the action sequence. Our goal is to compute action sequences that yield approximately optimal total value to the agents (a.k.a., social welfare). We assume query access to the value $v_i(S)$ that the agent i gets when she acts after the agents in the ordered set $S$. We establish tight bounds on the social welfare that can be achieved using polynomially many queries. Even though these bounds show a marginally sublinear approximation of optimal social welfare in general, excellent approximations can be obtained when the valuations stem from an underlying combinatorial domain. Indicatively, when the valuations are defined using bipartite matchings, arborescences in directed graphs, and satisfiability of Boolean expressions, simple query-efficient algorithms yield $2$-approximations. We discuss issues related to truthfulness and show how some of our algorithms can be implemented truthfully using VCG-like payments. Finally, we introduce and study the price of serial dictatorship, a notion that provides an optimistic measure of the quality of combinatorial optimization solutions generated by action sequences.

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