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

{"title":"Knightian self uncertainty in the vcg mechanism for unrestricted combinatorial auctions","authors":"A. Chiesa, S. Micali, Z. Zhu","doi":"10.1145/2600057.2602857","DOIUrl":"https://doi.org/10.1145/2600057.2602857","url":null,"abstract":"We study the social welfare performance of the VCG mechanism in the well-known and challenging model of self uncertainty initially put forward by Frank H. Knight and later formalized by Truman F. Bewley. Namely, the only information that each player i has about his own true valuation consists of a set of distributions, from one of which i's valuation has been drawn. We assume that each player knows his true valuation up to an additive inaccuracy δ, and study the social welfare performance of the VCG mechanism relative to δ > 0. Denoting by MSW the maximum social welfare, we have already shown in [Chiesa, Micali and Zhu 2012] that, even in single-good auctions, no mechanism can guarantee any social welfare greater than MSW / n in dominant strategies or ex-post Nash equilibrium strategies, where n is the number of players. In a separate paper [CMZ14], we have proved that for multi-unit auctions, where it coincides with the Vickrey mechanism, the VCG mechanism performs very well in (Knightian) undominated strategies. Namely, in an n-player m-unit auction, the Vickrey mechanism guarantees a social welfare ≥ - MSW - 2mδ, when each Knightian player chooses an arbitrary undominated strategy to bid in the auction. In this paper we focus on the social welfare performance of the VCG mechanism in unrestricted combinatorial auctions, both in undominated strategies and regret-minimizing strategies. (Indeed, both solution concepts naturally extend to the Knightian setting with player self uncertainty.) Our first theorem proves that, in an n-player m-good combinatorial auction, the VCG mechanism may produce outcomes whose social welfare is ≤ - MSW - ω(2m δ), even when n=2 and each player chooses an undominated strategy. We also geometrically characterize the set of undominated strategies in this setting. Our second theorem shows that the VCG mechanism performs well in regret-minimizing strategies: the guaranteed social welfare is ≥-MSW - 2min{m,n}δ if each player chooses a pure regret-minimizing strategy, and ≥- MSW - O(n2 δ) if mixed strategies are allowed. Finally, we prove a lemma bridging two standard models of rationality: utility maximization and regret minimization. A special case of our lemma implies that, in any game (Knightian or not), every implementation for regret-minimizing players also applies to utility-maximizing players who use regret ONLY to break ties among their undominated strategies. This bridging lemma thus implies that the VCG mechanism continues to perform very well also for the latter players.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123702007","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":"Strategic information platforms: selective disclosure and the price of \"free\"","authors":"Chen Hajaj, David Sarne","doi":"10.1145/2600057.2602864","DOIUrl":"https://doi.org/10.1145/2600057.2602864","url":null,"abstract":"This paper deals with platforms that provide agents easier access to the type of opportunities in which they are interested (e.g., eCommerce platforms, used cars bulletins and dating web-sites). We show that under various common service schemes, a platform can benefit from not necessarily listing all the opportunities with which it is familiar, even if there is no marginal cost for listing any additional opportunity. The main implication of this result is that platforms should extract their expected-profit-maximizing service terms not based solely on the fees charged from users, but they should also use the subset that will be listed as the decision variable in the optimization problem. The analysis applies to four well-known service schemes that a platform may use to price its services. We show that neither of these schemes generally dominates the others or is dominated by any of the others. For the common case of homogeneous preferences, however, several dominance relationships can be proved, enabling the platform to identify the schemes that should be used as a default. Furthermore, the analysis provides a game-theoretic search-based explanation for a possible preference of buyers to pay for the service rather than receive it for free (e.g., when the service is sponsored by ads), a phenomena that has been justified in prior literature typically with the argument of willingness to pay a premium for an ad-free experience or more reliable platforms. The paper shows that this preference can hold both for the users and the platform in a given setting, even if both sides are fully strategic.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"507 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122757039","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":"Incentivizing exploration","authors":"P. Frazier, D. Kempe, J. Kleinberg, Robert D. Kleinberg","doi":"10.1145/2600057.2602897","DOIUrl":"https://doi.org/10.1145/2600057.2602897","url":null,"abstract":"We study a Bayesian multi-armed bandit (MAB) setting in which a principal seeks to maximize the sum of expected time-discounted rewards obtained by pulling arms, when the arms are actually pulled by selfish and myopic individuals. Since such individuals pull the arm with highest expected posterior reward (i.e., they always exploit and never explore), the principal must incentivize them to explore by offering suitable payments. Among others, this setting models crowdsourced information discovery and funding agencies incentivizing scientists to perform high-risk, high-reward research. We explore the tradeoff between the principal's total expected time-discounted incentive payments, and the total time-discounted rewards realized. Specifically, with a time-discount factor γ ∈ (0,1), let OPT denote the total expected time-discounted reward achievable by a principal who pulls arms directly in a MAB problem, without having to incentivize selfish agents. We call a pair (ρ,b) ∈ [0,1]2 consisting of a reward ρ and payment b achievable if for every MAB instance, using expected time-discounted payments of at most b•OPT, the principal can guarantee an expected time-discounted reward of at least ρ•OPT. Our main result is an essentially complete characterization of achievable (payment, reward) pairs: if √b+√1-ρ>√γ, then (ρ,b) is achievable, and if √b+√1-ρ<√γ, then (ρ,b) is not achievable. In proving this characterization, we analyze so-called time-expanded policies, which in each step let the agents choose myopically with some probability p, and incentivize them to choose \"optimally\" with probability 1-p. The analysis of time-expanded policies leads to a question that may be of independent interest: If the same MAB instance (without selfish agents) is considered under two different time-discount rates γ > η, how small can the ratio of OPTη to OPTγ be? We give a complete answer to this question, showing that OPTη ≥ (1-γ)2/(1-η)2 • OPTγ, and that this bound is tight.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129838479","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 auctions for correlated buyers with sampling","authors":"Hu Fu, Nima Haghpanah, Jason D. Hartline, Robert D. Kleinberg","doi":"10.1145/2600057.2602895","DOIUrl":"https://doi.org/10.1145/2600057.2602895","url":null,"abstract":"Crémer and McLean [1985] showed that, when buyers' valuations are drawn from a correlated distribution, an auction with full knowledge on the distribution can extract the full social surplus. We study whether this phenomenon persists when the auctioneer has only incomplete knowledge of the distribution, represented by a finite family of candidate distributions, and has sample access to the real distribution. We show that the naive approach which uses samples to distinguish candidate distributions may fail, whereas an extended version of the Crémer-McLean auction simultaneously extracts full social surplus under each candidate distribution. With an algebraic argument, we give a tight bound on the number of samples needed by this auction, which is the difference between the number of candidate distributions and the dimension of the linear space they span.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129995062","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":"Misdirected search effort in a matching market: causes, consequences and a partial solution","authors":"J. Horton","doi":"10.1145/2600057.2602867","DOIUrl":"https://doi.org/10.1145/2600057.2602867","url":null,"abstract":"Using data from an online labor market, I show that buyers inefficiently pursue oversubscribed sellers. Although oversubscribed sellers are positively selected, this fact alone cannot account for the amount of attention they receive. \"Excess\" buyer attention is caused by an information asymmetry: buyers do not know seller capacities and cannot condition their search efforts accordingly. Sellers---having free disposal on buyer inquiries---have little incentive to disabuse searching buyers. This misdirected search effort is consequential: using an instrumental variables analysis, I show that a recruited seller rejecting a buyer's recruiting inquiry reduces the probability of match formation by as much as 67% points. Motivated by the empirical results, I show how the market-creating platform can optimally allocate buyer attention, given each seller's estimated per-encounter probability of forming a match.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115907362","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":"Individual security and network design","authors":"Diego A. Cerdeiro, M. Dziubiński, S. Goyal","doi":"10.1145/2600057.2602894","DOIUrl":"https://doi.org/10.1145/2600057.2602894","url":null,"abstract":"Individuals derive benefits from being connected to others: computer users benefit from sharing content, criminals benefit from cooperating. Connections, however, may transmit external threats. A virus may spread through a computer network. An investigation may dismantle entire criminal organization. Given agents’ individual incentives to protect, which network(s) should be chosen to maximize agents’ welfare? We consider the tension between the value of being connected and the exposure to contagion when a protection technology is available. There are (n + 2) ‘players’. The designer first chooses the network over the n nodes. Given this network, the nodes (simultaneously) choose whether to protect or not; protection is costly. Finally, the adversary chooses a node to attack. If the attacked node is not protected, then this node and all nodes with a path to the attacked node through unprotected nodes are eliminated. Nodes derive benefits from their connectivity: a surviving node gets, as a gross payoff, an equal share of the value of its surviving component. Component value is a convex and increasing function of its size. Node’s net payoffs are equal to its connectivity payoffs less the cost of protection. The designer seeks to maximize the sum of nodes’ payoffs. The adversary aims to minimize connectivity-related payoffs. The first best design and defence profile that a central planner would choose is as follows. For low costs, all nodes is protected and the network is connected. For intermediate costs, a centrally protected star is chosen. The adversary eliminates a spoke. If costs are high, protection is dropped and network is split into several components. The adversary removes a largest one. A number of problems arise for the designer when he cannot control defence decisions. First, a node does not internalize the benefits accruing to others from its own protection. Thus, it is possible that the center-","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116458332","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":"Reasoning about optimal stable matchings under partial information","authors":"Baharak Rastegari, A. Condon, Nicole Immorlica, Robert W. Irving, Kevin Leyton-Brown","doi":"10.1145/2600057.2602884","DOIUrl":"https://doi.org/10.1145/2600057.2602884","url":null,"abstract":"We study two-sided matching markets in which participants are initially endowed with partial preference orderings, lacking precise information about their true, strictly ordered list of preferences. We wish to reason about matchings that are stable with respect to agents' true preferences, and which are furthermore optimal for one given side of the market. We present three main results. First, one can decide in polynomial time whether there exists a matching that is stable and optimal under all strict preference orders that refine the given partial orders, and can construct this matching in polynomial time if it does exist. We show, however, that deciding whether a given pair of agents are matched in all or no such optimal stable matchings is co-NP-complete, even under quite severe restrictions on preferences. Finally, we describe a polynomial-time algorithm that decides, given a matching that is stable under the partial preference orderings, whether that matching is stable and optimal for one side of the market under some refinement of the partial orders.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124652186","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":"Differentially private and incentive compatible recommendation system for the adoption of network goods","authors":"Kevin He, Xiaosheng Mu","doi":"10.1145/2600057.2602841","DOIUrl":"https://doi.org/10.1145/2600057.2602841","url":null,"abstract":"We study the problem of designing a recommendation system for network goods under the constraint of differential privacy. Agents living on a graph face the introduction of a new good and undergo two stages of adoption. The first stage consists of private, random adoptions. In the second stage, remaining non-adopters decide whether to adopt with the help of a recommendation system A. The good has network complimentarity, making it socially desirable for A to reveal the adoption status of neighboring agents. The designer's problem, however, is to find the socially optimal A that preserves privacy. We derive feasibility conditions for this problem and characterize the optimal solution.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125057388","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":"Revealing and incorporating implicit communities to improve recommender systems","authors":"Euijin Choo, Ting Yu, Min Chi, Y. Sun","doi":"10.1145/2600057.2602906","DOIUrl":"https://doi.org/10.1145/2600057.2602906","url":null,"abstract":"Social connections often have a significant influence on personal decision making. Researchers have proposed novel recommender systems that take advantage of social relationship information to improve recommendations. These systems, while promising, are often hindered in practice. Existing social networks such as Facebook are not designed for recommendations and thus contain many irrelevant relationships. Many recommendation platforms such as Amazon often do not permit users to establish explicit social relationships. And direct integration of social and commercial systems raises privacy concerns. In this paper we address these issues by focusing on the extraction of implicit and relevant relationships among users based upon the patterns of their existing interactions. Our work is grounded in the context of item recommendations on Amazon. We investigate whether users' reply patterns can be used to identify these meaningful relationships and show that different degrees of relationships do exist. We develop global measures of relationship strength and observe that users tend to form strong connections when they are evaluating subjective items such as books and movies. We then design a probabilistic mechanism to distinguish meaningful connections from connections formed by chance and extract implicit communities. We finally show that these communities can be used for hybrid recommender systems that improve recommendations over existing collaborative filtering approaches.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126456698","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":"Mechanism with unique learnable equilibria","authors":"Paul Dütting, Thomas Kesselheim, É. Tardos","doi":"10.1145/2600057.2602838","DOIUrl":"https://doi.org/10.1145/2600057.2602838","url":null,"abstract":"The existence of a unique equilibrium is the classic tool for ensuring predictiveness of game theory. Typical uniqueness results, however, are for Nash and Bayes-Nash equilibria and do not guarantee that natural game playing dynamic converges to this equilibrium. In fact, there are well known examples in which the equilibrium is unique, yet natural learning behavior does not converge to it. Motivated by this, we strive for stronger uniqueness results. We do not only require that there is a unique equilibrium, but also that this equilibrium must be learnable. We adopt correlated equilibrium as our solution concept, as simple and natural learning algorithms guarantee that the empirical distribution of play converges to the space of correlated equilibria. Our main result is to show uniqueness of correlated equilibria in a large class of single-parameter mechanisms with matroid structure. We also show that our uniqueness result extends to problems with polymatroid structure under some conditions. Our model includes a number of special cases interesting on their own right, such as procurement auctions and Bertrand competitions. An interesting feature of our model is that we do not need to assume that the players have quasi-linear utilities, and hence can incorporate models with risk averse players and certain forms of externalities.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133614508","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}