J. Hatfield, S. Kominers, A. Nichifor, M. Ostrovsky, Alexander Westkamp
{"title":"Full Substitutability in Trading Networks","authors":"J. Hatfield, S. Kominers, A. Nichifor, M. Ostrovsky, Alexander Westkamp","doi":"10.1145/2764468.2764472","DOIUrl":"https://doi.org/10.1145/2764468.2764472","url":null,"abstract":"Various forms of substitutability are essential for establishing the existence of equilibria and other useful properties in diverse settings such as matching, auctions, and exchange economies with indivisible goods. In this paper, we extend earlier models' canonical definitions of substitutability to a setting in which an agent can be a buyer in some transactions and a seller in others, and show that all the different substitutability concepts are equivalent. Next, we introduce a new class of fully substitutable preferences that models the preferences of intermediaries with production capacity. We then prove that substitutability is preserved under economically important transformations such as trade endowments, mergers, and limited liability. We show that full substitutability can be recast in terms of submodularity of the indirect utility function, the single improvement property, a \"no complementarities\" condition, and a condition from discrete convex analysis called M♮-concavity. Finally, we show that substitutability implies two key monotonicity conditions known as the Laws of Aggregate Supply and Demand. All of our results explicitly incorporate economically important features such as indifferences, non-monotonicities, and unbounded utility functions that were not fully addressed in prior work.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"125 23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126816562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Designing Dynamic Contests","authors":"K. Bimpikis, S. Ehsani, Mohamed Mostagir","doi":"10.1145/2764468.2764473","DOIUrl":"https://doi.org/10.1145/2764468.2764473","url":null,"abstract":"Innovation contests have emerged as a viable alternative to the standard research and development process. They are particularly suited for settings that feature a high degree of uncertainty regarding the actual feasibility of the end goal. The objective of the contest designer is to maximize the probability of reaching the innovation goal while minimizing the time it takes to complete the project. Obviously here the important question is how to best design these contests. This paper departs from prior literature through three key modeling features. First, in our model, an agent's progress towards the goal is not a deterministic function of effort. As is typically the case in real-world settings, progress is positively correlated with effort but the mapping involves a stochastic component. Secondly and quite importantly, it is possible that the innovation in question is not attainable, either because the goal is actually infeasible or because it requires too much effort and resources that it makes little economic sense to pursue. We model such a scenario by having an underlying state of the world (whether the innovation is attainable or not) over which participants have some prior belief. Taken together, these two features imply that an agent's lack of progress may be attributed to either an undesirable underlying state (the innovation is not attainable) or simply to the fact that the agent was unlucky in how her effort was stochastically mapped to progress. Thirdly, we consider a dynamic framework that captures how competition between agents evolves over time and incorporates the fact that agents learn from each other's partial progress to discern the underlying reason for their own lack of progress. In particular, our modeling setup includes well-defined intermediate milestones that constitute partial progress towards the end goal.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127829697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Wisdom of Multiple Guesses","authors":"J. Ugander, Ryan Drapeau, Carlos Guestrin","doi":"10.1145/2764468.2764529","DOIUrl":"https://doi.org/10.1145/2764468.2764529","url":null,"abstract":"The \"wisdom of crowds\" dictates that aggregate predictions from a large crowd can be surprisingly accurate, rivaling predictions by experts. Crowds, meanwhile, are highly heterogeneous in their expertise. In this work, we study how the heterogeneous uncertainty of a crowd can be directly elicited and harnessed to produce more efficient aggregations from a crowd, or provide the same efficiency from smaller crowds. We present and evaluate a novel strategy for eliciting sufficient information about an individual's uncertainty: allow individuals to make multiple simultaneous guesses, and reward them based on the accuracy of their closest guess. We show that our multiple guesses scoring rule is an incentive-compatible elicitation strategy for aggregations across populations under the reasonable technical assumption that the individuals all hold symmetric log-concave belief distributions that come from the same location-scale family. We first show that our multiple guesses scoring rule is strictly proper for a fixed set of quantiles of any log-concave belief distribution. With properly elicited quantiles in hand, we show that when the belief distributions are also symmetric and all belong to a single location-scale family, we can use interquantile ranges to furnish weights for certainty-weighted crowd aggregation. We evaluate our multiple guesses framework empirically through a series of incentivized guessing experiments on Amazon Mechanical Turk, and find that certainty-weighted crowd aggregations using multiple guesses outperform aggregations using single guesses without certainty weights.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127353474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nikhil R. Devanur, Jamie Morgenstern, Vasilis Syrgkanis, S. Weinberg
{"title":"Simple Auctions with Simple Strategies","authors":"Nikhil R. Devanur, Jamie Morgenstern, Vasilis Syrgkanis, S. Weinberg","doi":"10.1145/2764468.2764484","DOIUrl":"https://doi.org/10.1145/2764468.2764484","url":null,"abstract":"We introduce single-bid auctions as a new format for combinatorial auctions. In single-bid auctions, each bidder submits a single real-valued bid for the right to buy items at a fixed price. Contrary to other simple auction formats, such as simultaneous or sequential single-item auctions, bidders can implement no-regret learning strategies for single-bid auctions in polynomial time. Price of anarchy bounds for correlated equilibria concepts in single-bid auctions therefore have more bite than their counterparts for auctions and equilibria for which learning is not known to be computationally tractable (or worse, known to be computationally intractable [Cai and Papadimitriou 2014; Dobzinski et al. 2015] this end, we show that for any subadditive valuations the social welfare at equilibrium is an O(log m)-approximation to the optimal social welfare, where $m$ is the number of items. We also provide tighter approximation results for several subclasses. Our welfare guarantees hold for Nash equilibria and no-regret learning outcomes in both Bayesian and complete information settings via the smooth-mechanism framework. Of independent interest, our techniques show that in a combinatorial auction setting, efficiency guarantees of a mechanism via smoothness for a very restricted class of cardinality valuations extend, with a small degradation, to subadditive valuations, the largest complement-free class of valuations.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116920149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maria-Florina Balcan, Avrim Blum, Nika Haghtalab, A. Procaccia
{"title":"Commitment Without Regrets: Online Learning in Stackelberg Security Games","authors":"Maria-Florina Balcan, Avrim Blum, Nika Haghtalab, A. Procaccia","doi":"10.1145/2764468.2764478","DOIUrl":"https://doi.org/10.1145/2764468.2764478","url":null,"abstract":"In a Stackelberg Security Game, a defender commits to a randomized deployment of security resources, and an attacker best-responds by attacking a target that maximizes his utility. While algorithms for computing an optimal strategy for the defender to commit to have had a striking real-world impact, deployed applications require significant information about potential attackers, leading to inefficiencies. We address this problem via an online learning approach. We are interested in algorithms that prescribe a randomized strategy for the defender at each step against an adversarially chosen sequence of attackers, and obtain feedback on their choices (observing either the current attacker type or merely which target was attacked). We design no-regret algorithms whose regret (when compared to the best fixed strategy in hindsight) is polynomial in the parameters of the game, and sublinear in the number of times steps.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131671059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Procurement Mechanisms for Differentiated Products","authors":"D. Sabán, G. Weintraub","doi":"10.1145/2764468.2764520","DOIUrl":"https://doi.org/10.1145/2764468.2764520","url":null,"abstract":"We consider the problem faced by a procurement agency that runs an auction-type mechanism to construct an assortment of products with posted prices, from a set of differentiated products offered by strategic suppliers. Heterogeneous consumers then buy their most preferred alternative from the assortment as needed. Framework agreements (FAs), widely used in the public sector, take this form; the central government runs the initial auction and then the public organizations (hospitals, schools, etc.) buy from the selected assortment. This type of mechanism is also relevant in other contexts, such as the design of medical formularies and group buying. When evaluating the bids, the procurement agency must consider the optimal trade-off between offering a richer assortment of products for consumers versus offering less variety, hoping to engage the suppliers in a more aggressive price competition. We develop a mechanism design approach to study this problem and provide a characterization of the optimal assortments and prices. The optimal mechanism balances the trade-off between product variety and price competition, in terms of suppliers' costs, products' characteristics, and consumers' characteristics. Relative to the traditional mechanism design problem, a distinctive feature of our formulation is that the auctioneer cannot directly decide how to allocate demand across products. Instead, the auctioneer selects the assortment and prices, and demands are then determined by the underlying preferences of consumers. Our work advances the theory of auctions and mechanism design by accounting for an endogenous demand system for differentiated products. We then use the optimal mechanism as a benchmark to evaluate the performance of the Chilean government procurement agency's current implementation of FAs, used to acquire US$2 billion worth of goods per year. We show how simple modifications to the current mechanism, which increase price competition among close substitutes, can considerably improve performance.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134601748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adverse Selection and Auction Design for Internet Display Advertising","authors":"N. Arnosti, M. Beck, Paul R. Milgrom","doi":"10.2139/ssrn.2603336","DOIUrl":"https://doi.org/10.2139/ssrn.2603336","url":null,"abstract":"We model an online display advertising environment with brand advertisers and better-informed performance advertisers, and seek an auction mechanism that is strategy-proof, anonymous and insulates brand advertisers from adverse selection. We find that the only such mechanism that is also false-name proof assigns the item to the highest bidding performance advertiser only when the ratio of the highest bid to the second highest bid is sufficiently large. For fat-tailed match-value distributions, this new mechanism captures most of the gains from good matching and improves match values substantially compared to the common practice of setting aside impressions in advance.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126224913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Why Prices Need Algorithms","authors":"T. Roughgarden, Inbal Talgam-Cohen","doi":"10.1145/2764468.2764515","DOIUrl":"https://doi.org/10.1145/2764468.2764515","url":null,"abstract":"Understanding when equilibria are guaranteed to exist is a central theme in economic theory, seemingly unrelated to computation. This paper shows that the existence of pricing equilibria is inextricably connected to the computational complexity of related optimization problems: demand oracles, revenue-maximization, and welfare-maximization. This relationship implies, under suitable complexity assumptions, a host of impossibility results. We also suggest a complexity-theoretic explanation for the lack of useful extensions of the Walrasian equilibrium concept: such extensions seem to require the invention of novel polynomial-time algorithms for welfare-maximization.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126404085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Masahiro Goto, F. Kojima, Ryoji Kurata, A. Tamura, M. Yokoo
{"title":"Designing Matching Mechanisms under General Distributional Constraints","authors":"Masahiro Goto, F. Kojima, Ryoji Kurata, A. Tamura, M. Yokoo","doi":"10.1145/2764468.2764501","DOIUrl":"https://doi.org/10.1145/2764468.2764501","url":null,"abstract":"In this paper, we consider two-sided, many-to-one matching problems where agents in one side of the market (schools) impose some distributional constraints (e.g., a maximum quota for a set of schools), and develop a strategyproof mechanism that can handle a very general class of distributional constraints. We assume distributional constraints are imposed on a vector, where each element is the number of contracts accepted for each school. The only requirement we impose on distributional constraints is that the family of vectors that satisfy distributional constraints must be hereditary, which means if a vector satisfies the constraints, any vector that is smaller than it also satisfies them. When distributional constraints are imposed, a stable matching may not exist. We develop a strategyproof mechanism called Adaptive Deferred Acceptance mechanism (ADA), which is nonwasteful and \"more fair\" than a simple nonwasteful mechanism called the Serial Dictatorship mechanism (SD) and \"less wasteful\" than another simple fair mechanism called the Artificial Cap Deferred Acceptance mechanism (ACDA). We show that we can apply this mechanism even if the distributional constraints do not satisfy the hereditary condition by applying a simple trick, assuming we can find a vector that satisfy the distributional constraints efficiently. Furthermore, we demonstrate the applicability of our model in actual application domains.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133701042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan
{"title":"Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets","authors":"Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan","doi":"10.1145/2764468.2764532","DOIUrl":"https://doi.org/10.1145/2764468.2764532","url":null,"abstract":"We provide the first concrete algorithm for combining market makers and limit orders in a prediction market with continuous trade. Our mechanism is general enough to handle both bundle orders and arbitrary securities defined over combinatorial outcome spaces. We define the notion of an e-fair trading path, a path in security space along which no order executes at a price more than e above its limit, and every order executes when its market price falls more than e below its limit. We show that, under a certain supermodularity condition, a fair trading path exists for which the endpoint is efficient, but that under general conditions reaching an efficient endpoint via an e-fair trading path is not possible. We develop an algorithm for operating a continuous market maker with limit orders that respects the e-fairness conditions in the general case. We conduct simulations of our algorithm using real combinatorial predictions made during the 2008 US presidential election and evaluate it against a natural baseline according to trading volume, social welfare, and violations of the two fairness conditions.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116075481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}