Proceedings of the fifteenth ACM conference on Economics and computation最新文献

{"title":"Generalized second price auction with probabilistic broad match","authors":"Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang","doi":"10.1145/2600057.2602828","DOIUrl":"https://doi.org/10.1145/2600057.2602828","url":null,"abstract":"Generalized Second Price (GSP) auctions are widely used by search engines today to sell their ad slots. Most search engines have supported the broad match between queries and bid keywords when executing the GSP auctions, however, it has been revealed that the GSP auction with the standard broad-match mechanism they are currently using (denoted as SBM-GSP) has several theoretical drawbacks (e.g., its theoretical properties are known only for the single-slot case and full-information setting, and even in this simple setting, the corresponding worst-case social welfare can be rather bad). To address this issue, we propose a novel broad-match mechanism, which we call the Probabilistic Broad-Match (PBM) mechanism. Different from SBM that puts together the ads bidding on all the keywords matched to a given query for the GSP auction, the GSP with PBM (denoted as PBM-GSP) randomly samples a keyword according to a predefined probability distribution and only runs the GSP auction for the ads bidding on this sampled keyword. We perform a comprehensive study on the theoretical properties of the PBM-GSP. Specifically, we study its social welfare in the worst equilibrium, in both full-information and Bayesian settings. The results show that PBM-GSP can generate larger welfare than SBM-GSP} under mild conditions. Furthermore, we also study the revenue guarantee for PBM-GSP in Bayesian setting. To the best of our knowledge, this is the first work on broad-match mechanisms for GSP that goes beyond the single-slot case and the full-information setting.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129426207","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":"Incentivized optimal advert assignment via utility decomposition","authors":"F. Kelly, P. Key, N. Walton","doi":"10.1145/2600057.2602849","DOIUrl":"https://doi.org/10.1145/2600057.2602849","url":null,"abstract":"We consider a large-scale Ad-auction where adverts are assigned over a potentially infinite number of searches. We capture the intrinsic asymmetries in information between advertisers, the advert platform and the space of searches: advertisers know and can optimize the average performance of their advertisement campaign; the platform knows and can optimize on each search instance; and, neither party knows the distribution of the infinite number of searches that can occur. We look at maximizing the aggregate utility of the click-through rates of advertisers subject to the matching constraints of online ad allocation. We show that this optimization can be decomposed into subproblems, which occur on timescales relevant to the platform or the advertisers respectively. The interpretation of the subproblems is that advertisers choose prices which are optimal given the average click-through rate they receive, that the platform allocates adverts according to a classical assignment problem per search impression and that prices satisfy a nominal complementary slackness condition. We then place this optimization result in a game-theoretic framework by assuming that advertisers bid strategically to maximize their net benefit. In this setting, we construct a mechanism with a unique Nash equilibrium that achieves the decomposition just described, and thus maximizes aggregate utility. This simple and implementable mechanism is as follows. When a search occurs, the platform allocates advertisement slots in order to maximize the expected bid from a click-throughs - this is a classical assignment problem. If an advert receives a click, the platform then solves the assignment problem a second time with the advertiser's bid replaced by a bid which is uniformly distributed between zero and the original bid. The advertiser is then charged their bid minus a rebate. The rebate is the product of the advertiser's bid and ratio of the advertiser's click-through rate in the second assignment calculation (after a click-through) to the first assignment click-through rate (before the click-through). We demonstrate that, under the assignment and pricing mechanism just described, advertisers bidding strategically will maximize aggregate utility. The novelty of the mechanism just described is that, while maximizing utilitarian objective, it can be implemented by the platform in a strategic environment on the time-scales relevant to the platform (per-impression) and advertiser (on-average) respectively, and neither party requires information on the distribution of searches. We also show that dynamic models, where advertisers adapt their bids smoothly over time, will converge to the solution that maximizes aggregate utility.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125343753","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":"Duality and optimality of auctions for uniform distributions","authors":"Y. Giannakopoulos, E. Koutsoupias","doi":"10.1145/2600057.2602883","DOIUrl":"https://doi.org/10.1145/2600057.2602883","url":null,"abstract":"We derive exact optimal solutions for the problem of optimizing revenue in single-bidder multi-item auctions for uniform i.i.d. valuations. We give optimal auctions of up to 6 items; previous results were only known for up to three items. To do so, we develop a general duality framework for the general problem of maximizing revenue in many-bidders multi-item additive Bayesian auctions with continuous probability valuation distributions. The framework extends linear programming duality and complementarity to constraints with partial derivatives. The dual system reveals the geometric nature of the problem and highlights its connection with the theory of bipartite graph matchings. The duality framework is used not only for proving optimality, but perhaps more importantly, for deriving the optimal auction; as a result, the optimal auction is defined by natural geometric constraints.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125984941","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":"Bandits with concave rewards and convex knapsacks","authors":"Shipra Agrawal, Nikhil R. Devanur","doi":"10.1145/2600057.2602844","DOIUrl":"https://doi.org/10.1145/2600057.2602844","url":null,"abstract":"In this paper, we consider a very general model for exploration-exploitation tradeoff which allows arbitrary concave rewards and convex constraints on the decisions across time, in addition to the customary limitation on the time horizon. This model subsumes the classic multi-armed bandit (MAB) model, and the Bandits with Knapsacks (BwK) model of Badanidiyuru et al.[2013]. We also consider an extension of this model to allow linear contexts, similar to the linear contextual extension of the MAB model. We demonstrate that a natural and simple extension of the UCB family of algorithms for MAB provides a polynomial time algorithm that has near-optimal regret guarantees for this substantially more general model, and matches the bounds provided by Badanidiyuru et al.[2013] for the special case of BwK, which is quite surprising. We also provide computationally more efficient algorithms by establishing interesting connections between this problem and other well studied problems/algorithms such as the Blackwell approachability problem, online convex optimization, and the Frank-Wolfe technique for convex optimization. We give examples of several concrete applications, where this more general model of bandits allows for richer and/or more efficient formulations of the problem.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"162 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114105824","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":"Information aggregation in exponential family markets","authors":"Jacob D. Abernethy, Sindhu Kutty, Sébastien Lahaie, Rahul Sami","doi":"10.1145/2600057.2602896","DOIUrl":"https://doi.org/10.1145/2600057.2602896","url":null,"abstract":"We consider the design of prediction market mechanisms known as automated market makers. We show that we can design these mechanisms via the mold of exponential family distributions, a popular and well-studied probability distribution template used in statistics. We give a full development of this relationship and explore a range of benefits. We draw connections between the information aggregation of market prices and the belief aggregation of learning agents that rely on exponential family distributions. We develop a natural analysis of the market behavior as well as the price equilibrium under the assumption that the traders exhibit risk aversion according to exponential utility. We also consider similar aspects under alternative models, such as budget-constrained traders.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131676084","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":"Dynamic matching market design","authors":"M. Akbarpour, Shengwu Li, S. Gharan","doi":"10.1145/2600057.2602887","DOIUrl":"https://doi.org/10.1145/2600057.2602887","url":null,"abstract":"We introduce a simple benchmark model of dynamic matching in networked markets, where agents arrive and depart stochastically and the network of acceptable transactions between agents forms a random graph. We analyze our model from three perspectives: waiting time, optimization, and information. The main insight of our analysis is that waiting to thicken the market can be substantially more important than increasing the speed of transactions, and this is quite robust to the presence of waiting costs. From an optimization perspective, naive local algorithms, that choose the right time to match agents but do not exploit global network structure, can perform very close to optimal algorithms. From an information perspective, algorithms that employ even partial information on agents' departure times perform substantially better than those that lack such information. Information and waiting are complements; information about departure times is necessary for waiting to yield large gains. To elicit agents' departure times, we design an incentive-compatible continuous-time dynamic mechanism without transfers. LINK: www.ssrn.com/abstract=2394319","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128197074","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":"Routing and staffing when servers are strategic","authors":"R. Gopalakrishnan, Sherwin Doroudi, Amy R. Ward, A. Wierman","doi":"10.1145/2600057.2602831","DOIUrl":"https://doi.org/10.1145/2600057.2602831","url":null,"abstract":"Traditionally, research focusing on the design of routing and staffing policies for service systems has modeled servers as having fixed (possibly heterogeneous) service rates. However, service systems are generally staffed by people. Furthermore, people respond to workload incentives; that is, how hard a person works can depend both on how much work there is, and how the work is divided between the people responsible for it. In a service system, the routing and staffing policies control such workload incentives; and so the rate servers work will be impacted by these policies. This observation has consequences when modeling service system performance, and our objective in this paper is to investigate those consequences. We do this in the context of the M/M/N queue, which is the canonical model for large service systems. First, we present a model for \"strategic\" servers that choose their service rate, in which there is a trade-off between an \"effort cost\" and a \"value of idleness\": faster service rates require more exertion of effort, but also lead to more idle time. Next, we characterize the symmetric Nash equilibrium service rate under any routing policy that routes based on the server idle time (such as the Longest Idle Server First policy). This allows us to (asymptotically) solve the problem of minimizing the total cost, when there are linear staffing costs and linear waiting costs. We find that an asymptotically optimal staffing policy staffs strictly more than the common square-root staffing policy. Finally, we end by exploring the question of whether routing policies that are based on the service rate, instead of the server idle time, can improve system performance.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125759655","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":"An axiomatic approach to characterizing and relaxing strategyproofness of one-sided matching mechanisms","authors":"Timo Mennle, Sven Seuken","doi":"10.1145/2600057.2602885","DOIUrl":"https://doi.org/10.1145/2600057.2602885","url":null,"abstract":"We study one-sided matching mechanisms where agents have vNM utility functions and report ordinal preferences. We first show that in this domain strategyproof mechanisms are characterized by three intuitive axioms: swap monotonicity, upper invariance, and lower invariance. Our second result is that dropping lower invariance leads to an interesting new relaxation of strategyproofness, which we call partial strategyproofness. In particular, we show that mechanisms are swap monotonic and upper invariant if and only if they are strategyproof on a restricted domain where agents have sufficiently different valuations for different objects. Furthermore, we show that this domain restriction is maximal and use it to define a single-parameter measure for the degree of strategyproofness of a manipulable mechanism. We also provide an algorithm that computes this measure. Our new partial strategyproofness concept finds applications in the incentive analysis of non-strategyproof mechanisms, such as the Probabilistic Serial mechanism, different variants of the Boston mechanism, and the construction of new hybrid mechanisms.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116970682","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 empirical implications of privacy-aware choice","authors":"Rachel Cummings, F. Echenique, A. Wierman","doi":"10.1145/2600057.2602830","DOIUrl":"https://doi.org/10.1145/2600057.2602830","url":null,"abstract":"This paper initiates the study of the testable implications of choice data in settings where agents have privacy preferences. We adapt the standard conceptualization of consumer choice theory to a situation where the consumer is aware of, and has preferences over, the information revealed by her choices. The main message of the paper is that little can be inferred about consumers' preferences once we introduce the possibility that the consumer has concerns about privacy. This holds even when consumers' privacy preferences are assumed to be monotonic and separable. This motivates the consideration of stronger assumptions and, to that end, we introduce an additive model for privacy preferences that does have testable implications.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124200101","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":"Optimal mechanisms with simple menus","authors":"Zihe Wang, Pingzhong Tang","doi":"10.1145/2600057.2602863","DOIUrl":"https://doi.org/10.1145/2600057.2602863","url":null,"abstract":"We consider revenue-optimal mechanism design for the case with one buyer and two items. The buyer's valuations towards the two items are independent and additive. In this setting, optimal mechanism is unknown for general valuation distributions. We obtain two categories of structural results that shed light on the optimal mechanisms. These results can be summarized into one conclusion: under certain conditions, the optimal mechanisms have simple menus. The first category of results state that, under a centain condition, the optimal mechanism has a monotone menu. In other words, in the menu that represents the optimal mechanism, as payment increases, the allocation probabilities for both items increase simultaneously. This theorem complements Hart and Reny's recent result regarding the nonmonotonicity of menu and revenue in multi-item settings. Applying this theorem, we derive a version of revenue monotonicity theorem that states stochastically superior distributions yield more revenue. Moreover, our theorem subsumes a previous result regarding sufficient conditions under which bundling is optimal[Hart and Nisan 2012]. The second category of results state that, under certain conditions, the optimal mechanisms have few menu items. Our first result in this category says that, for certain distributions, the optimal menu contains at most 4 items. The condition admits power (including uniform) density functions. Our second result in this category works for a weaker (hence more general) condition, under which the optimal menu contains at most 6 items. This condition is general enough to include a wide variety of density functions, such as exponential functions and any function whose Taylor series coefficients are nonnegative. Our last result in this category works for unit-demand setting. It states that, for uniform distributions, the optimal menu contains at most 5 items. All these results are in sharp contrast to Hart and Nisan's recent result that finite-sized menu cannot guarantee any positive fraction of optimal revenue for correlated valuation distributions.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122761229","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}