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.

The ACM Transactions on Economics and Computation welcomes submissions of the highest quality that explore the intersection of computer science and economics. The journal is interested in topics relevant to both economists and computer scientists, including but not limited to: agents in networks, algorithmic game theory, computation of equilibria, computational social choice, the cost of strategic behavior and 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, and systems resilient against malicious agents.

《ACM Transactions on Economics and Computation》欢迎提交高质量的论文，探讨计算机科学与经济学的交叉领域。期刊关注的主题包括但不限于：网络中的代理、算法博弈论、均衡计算、计算社会选择、战略行为和去中心化的成本（"无序价格"）、电子市场的设计与分析、计算广告的经济学、电子商务、游戏与市场中的学习、机制设计、付费搜索拍卖、隐私、推荐/声誉/信任系统，以及抵御恶意代理的系统。

ACM Transactions on Economics and Computation

We consider a dynamic auction model, where bidders sequentially arrive to the market. The values of the bidders for the item for sale are independently drawn from a distribution, but this distribution is unknown to the seller. The seller offers a personalized take-it-or-leave-it price for each arriving bidder and aims to maximize revenue. We study how well can such sequential posted-price mechanisms approximate the optimal revenue that would be achieved if the distribution was known to the seller. On the negative side, we show that sequential posted-price mechanisms cannot guarantee a constant fraction of this revenue when the class of candidate distributions is unrestricted. We show that this impossibility holds even for randomized mechanisms and even if the set of possible distributions is very small or when the seller has a prior distribution over the candidate distributions. On the positive side, we devise a simple posted-price mechanism that guarantees a constant fraction of the known-distribution revenue when all candidate distributions exhibit the monotone hazard rate property.

Moshe Babaioff

Liad Blumrosen

Shaddin Dughmi

Yaron Singer

Posting Prices with Unknown Distributions

发布价格与未知分布

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from truthfulness; it is not incorporated in players’ utility functions (and doing so has been shown to lead to nontruthfulness in some cases). In this work, we propose a new, general way of modeling privacy in players’ utility functions. Specifically, we only assume that if an outcome o has the property that any report of player i would have led to o with approximately the same probability, then o has a small privacy cost to player i . We give three mechanisms that are truthful with respect to our modeling of privacy: for an election between two candidates, for a discrete version of the facility location problem, and for a general social choice problem with discrete utilities (via a VCG-like mechanism). As the number n of players increases, the social welfare achieved by our mechanisms approaches optimal (as a fraction of n ).

Yiling Chen

Stephen Chong

Ian A. Kash

Tal Moran

Salil Vadhan

Truthful Mechanisms for Agents That Value Privacy

面向重视隐私的代理的真实机制

Bipartite-matching markets pair agents on one side of a market with agents, items, or contracts on the opposing side. Prior work addresses online bipartite-matching markets, where agents arrive over time and are dynamically matched to a known set of disposable resources. In this article, we propose a new model, Online Matching with (offline) Reusable Resources under Known Adversarial Distributions ( OM-RR-KAD ) , in which resources on the offline side are reusable instead of disposable; that is, once matched, resources become available again at some point in the future. We show that our model is tractable by presenting an LP-based non-adaptive algorithm that achieves an online competitive ratio of ½-ϵ for any given constant ϵ &gt; 0. We also show that no adaptive algorithm can achieve a ratio of ½ + o (1) based on the same benchmark LP. Through a data-driven analysis on a massive openly available dataset, we show our model is robust enough to capture the application of taxi dispatching services and ride-sharing systems. We also present heuristics that perform well in practice.

John P. Dickerson

Karthik A. Sankararaman

Aravind Srinivasan

Pan Xu

Allocation Problems in Ride-sharing Platforms

拼车平台中的分配问题

In this study, we propose a polyhedral clinching auction for indivisible goods, which has so far been studied for divisible goods. As in the divisible setting by Goel et al. (2015), our mechanism enjoys incentive compatibility, individual rationality, and Pareto optimality, and works with polymatroidal environments. A notable feature of this mechanism for the indivisible setting is that the entire procedure can be conducted in time polynomial of the number of buyers and goods. Moreover, we show additional efficiency guarantees, recently established by Sato for the divisible setting: the liquid welfare (LW) of our mechanism achieves more than half of the optimal LW, and the social welfare is more than the optimal LW.

Hiroshi Hirai

Ryosuke Sato

Polyhedral Clinching Auctions for Indivisible Goods

不可分商品的多面体压铆拍卖

We study deviations by a group of agents in the three main types of matching markets: the house allocation, the marriage, and the roommates models. For a given instance, we call a matching k -stable if no other matching exists that is more beneficial to at least k out of the n agents. The concept generalizes the recently studied majority stability [57]. We prove that whereas the verification of k -stability for a given matching is polynomial-time solvable in all three models, the complexity of deciding whether a k -stable matching exists depends on \(\frac{k}{n} \) and is characteristic to each model.

Haris Aziz

Gergely Csáji

Agnes Cseh

Computational complexity of <i>k</i> -stable matchings

<i>k</i> 稳定匹配的计算复杂度

We evaluate the fairness of a rule allocating among agents with equal rights by computing their utility for a hypothetical worst-case share, that only depends on their own valuation and the number of agents. For indivisible goods, Budish [J. Political Econ., 2011] proposed the maximin share : the least utility of a bundle in the best partition of the objects; unfortunately maximin share is not always satisfiable. Earlier, Hill [Ann. Probab., 1987] proposed the worst maximin share over all utilities with the same largest possible single-object value. More conservative than maximin share, it is guaranteed to be satisfiable for any possible profile of utilities and its computation is elementary whereas it is NP-hard to compute maximin share. We apply Hill’s approach to the allocation of indivisible bads (objects with disutilities) and compute in closed form the worst-case minimax share for a given value of the worst single bad. We show that the worst-case minimax share is close to the original minimax share and that its monotonic closure is the best guaranteed share for all allocation instances with a common upper bound on the value of the worst single bad.

Bo Li

Herve Moulin

Ankang Sun

Yu Zhou

On Hill's Worst-Case Guarantee for Indivisible Bads

关于不可分坏品的希尔最坏情况保证

In a game of persuasion with evidence, a sender has private information. By presenting evidence on the information, the sender wishes to persuade a receiver to take a single action (e.g., hire a job candidate, or convict a defendant). The sender’s utility depends solely on whether or not the receiver takes the action. The receiver’s utility depends on both the action and the sender’s private information. We study three natural variations. First, we consider the problem of computing an equilibrium of the game without commitment power. Second, we consider a persuasion variant, where the sender commits to a signaling scheme and the receiver, after seeing the evidence, takes the action or not. Third, we study a delegation variant, where the receiver first commits to taking the action if being presented certain evidence, and the sender presents evidence to maximize the probability the action is taken. We study these variants through the computational lens, and give hardness results, optimal approximation algorithms, and polynomial-time algorithms for special cases. Among our results is an approximation algorithm that rounds a semidefinite program that might be of independent interest, since, to the best of our knowledge, it is the first such approximation algorithm in algorithmic economics.

Martin Hoefer

Pasin Manurangsi

Alexandros Psomas

Algorithmic Persuasion with Evidence

基于证据的算法说服

Many two-sided platforms are known to steer customers towards certain products based on their willingness to pay. In this article, we study platforms’ incentives to adopt this type of market segmentation and present conditions under which this can generate distortions that negatively impact the surplus from buyers and sellers. In our environment, a monopolistic platform matches sellers with buyers. Upon being matched, each pair of buyer and seller negotiates prices. If they choose to transact, the platform receives a commission fee proportional to the value of the transaction plus a flat fee per transaction. The platform is assumed to have full information about customers’ and sellers’ outside options. We show that, as long as the market is in excess supply or as long as there is a crossing between the demand and supply curves , the platform’s optimal matching is suboptimal from the perspective of buyers and sellers.

Pedro Vaissman Guinsburg

Gustavo Quinderé Saraiva

Search Steering in Two-Sided Platforms

双边平台中的搜索引导

Abbreviation	ACM Trans. Econ. Comput.
Journal Impact	1.09
Quartiles(Global)	COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS(Q4)

ISSN	2167-8375, 2167-8383
h-index	23

Publication Information	Publisher: Association for Computing Machinery (ACM)，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2013，Proportion of original research papers: 100.00%，Self Citation Rate:0.00%， Gold OA Rate: 2.08%

ACM Transactions on Economics and Computation

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Share Submission Experience

Posting Prices with Unknown Distributions

Truthful Mechanisms for Agents That Value Privacy

Allocation Problems in Ride-sharing Platforms

Polyhedral Clinching Auctions for Indivisible Goods

Computational complexity of k -stable matchings

Polyhedral Clinching Auctions for Indivisible Goods

Computational complexity of k -stable matchings

On Hill's Worst-Case Guarantee for Indivisible Bads

Algorithmic Persuasion with Evidence

Search Steering in Two-Sided Platforms