160 research outputs found

    Auctions and bidding: A guide for computer scientists

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    There is a veritable menagerie of auctions-single-dimensional, multi-dimensional, single-sided, double-sided, first-price, second-price, English, Dutch, Japanese, sealed-bid-and these have been extensively discussed and analyzed in the economics literature. The main purpose of this article is to survey this literature from a computer science perspective, primarily from the viewpoint of computer scientists who are interested in learning about auction theory, and to provide pointers into the economics literature for those who want a deeper technical understanding. In addition, since auctions are an increasingly important topic in computer science, we also look at work on auctions from the computer science literature. Overall, our aim is to identifying what both these bodies of work these tell us about creating electronic auctions. © 2011 ACM.This work was funded in part by HP under the “Always on” grant, by NSF IIS-0329037 “Tools and Techniques for Automated Mechanism Design”, and by IEA (TIN2006-15662-C02-01), OK (IST-4-027253-STP), eREP(EC-FP6-CIT5-28575) and Agreement Technologies (CONSOLIDER CSD2007-0022, INGENIO 2010).Peer Reviewe

    Proportional Fairness and Strategic Behaviour in Facility Location Problems

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    The one-dimensional facility location problem readily generalizes to many real world problems, including social choice, project funding, and the geographic placement of facilities intended to serve a set of agents. In these problems, each agent has a preferred point along a line or interval, which could denote their ideal preference, preferred project funding, or location. Thus each agent wishes the facility to be as close to their preferred point as possible. We are tasked with designing a mechanism which takes in these preferred points as input, and outputs an ideal location to build the facility along the line or interval domain. In addition to minimizing the distance between the facility and the agents, we may seek a facility placement which is fair for the agents. In particular, this thesis focusses on the notion of proportional fairness, in which endogenous groups of agents with similar or identical preferences have a distance guarantee from the facility that is proportional to the size of the group. We also seek mechanisms that are strategyproof, in that no agent can improve their distance from the facility by lying about their location. We consider both deterministic and randomized mechanisms, in both the classic and obnoxious facility location settings. The obnoxious setting differs from the classic setting in that agents wish to be far from the facility rather than close to it. For these settings, we formalize a hierarchy of proportional fairness axioms, and where possible, characterize strategyproof mechanisms which satisfy these axioms. In the obnoxious setting where this is not possible, we consider the welfare-optimal mechanisms which satisfy these axioms, and quantify the extent at which the system efficiency is compromised by misreporting agents. We also investigate, in the classic setting, the nature of misreporting agents under a family of proportionally fair mechanisms which are not necessarily strategyproof. These results are supplemented with tight approximation ratio and price of fairness bounds which provide further insight into the compromise between proportional fairness and efficiency in the facility location problem. Finally, we prove basic existence results concerning possible extensions to our settings

    Search and optimization with randomness in computational economics: equilibria, pricing, and decisions

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    In this thesis we study search and optimization problems from computational economics with primarily stochastic inputs. The results are grouped into two categories: First, we address the smoothed analysis of Nash equilibrium computation. Second, we address two pricing problems in mechanism design, and solve two economically motivated stochastic optimization problems. Computing Nash equilibria is a central question in the game-theoretic study of economic systems of agent interactions. The worst-case analysis of this problem has been studied in depth, but little was known beyond the worst case. We study this problem in the framework of smoothed analysis, where adversarial inputs are randomly perturbed. We show that computing Nash equilibria is hard for 2-player games even when input perturbations are large. This is despite the existence of approximation algorithms in a similar regime. In doing so, our result disproves a conjecture relating approximation schemes to smoothed analysis. Despite the hardness results in general, we also present a special case of co-operative games, where we show that the natural greedy algorithm for finding equilibria has polynomial smoothed complexity. We also develop reductions which preserve smoothed analysis. In the second part of the thesis, we consider optimization problems which are motivated by economic applications. We address two stochastic optimization problems. We begin by developing optimal methods to determine the best among binary classifiers, when the objective function is known only through pairwise comparisons, e.g. when the objective function is the subjective opinion of a client. Finally, we extend known algorithms in the Pandora's box problem --- a classic optimal search problem --- to an order-constrained setting which allows for richer modelling. The remaining chapters address two pricing problems from mechanism design. First, we provide an approximately revenue-optimal pricing scheme for the problem of selling time on a server to jobs whose parameters are sampled i.i.d. from an unknown distribution. We then tackle the problem of fairly dividing chores among a collection of economic agents via a competitive equilibrium, which balances assigned tasks with payouts. We give efficient algorithms to compute such an equilibrium

    Approaches to mechanism design with boundedly rational agents

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2012.Cataloged from PDF version of thesis.Includes bibliographical references.This dissertation ties together three papers on mechanism design with boundedly rational agents. These papers explore theoretically whether, and to what extent, limitations on agents' ability to strategically misrepresent their preferences can help a mechanism designer achieve outcomes that she could not achieve with perfectly rational agents. The first chapter investigates whether local incentive constraints are sufficient to logically imply full incentive-compatibility, in a variety of mechanism design settings. This can be motivated by a boundedly rational model in which agents cannot contemplate all possible misrepresentations, but can consider those that are close to their true preferences. This chapter offers a unified approach that covers both continuous and discrete type spaces, showing that in many commonly studied cases, local incentive-compatibility (suitably defined) implies full incentive-compatibility. The second chapter advances the methodology of looking quantitatively at incentives for strategic behavior, motivated by the premise that agents will be truthful if the incentive to be strategic is small enough. This chapter defines a mechanism's susceptibility to manipulation as the maximum amount of expected utility any agent can ever gain from strategic misrepresntation. This measure of susceptibility is then applied to anonymous voting rules. One set of results estimates the susceptibility of specific voting rules; an important finding is that several voting systems previously identified as resistant to manipulation are actually more susceptible than simple plurality rule, by the measure proposed here. A second set of results gives asymptotic lower bounds on susceptibility for any possible voting rule, under various combinations of efficiency, regularity, and informational conditions. These results illustrate how one can quantitatively explore the tradeoffs between susceptibility and other properties of the voting rule. The third chapter carries the methodology of the second chapter to a market environment: unit-demand, private-value double auction markets. This chapter quantitatively studies the tradeoff between inefficiency and susceptibility to manipulation, among all possible mechanisms for such markets. The main result approximately locates the possibility frontier, pinning it down within a factor that is logarithmic in the size of the market.by Gabriel D. Carroll.Ph.D

    Mass Customization of Cloud Services - Engineering, Negotiation and Optimization

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    Several challenges hinder the entry of mass customization principles into Cloud computing: Firstly, the service engineering on provider side needs to be automated. Secondly, there has to be a suitable negotiation mechanism helping provider and consumer on finding an agreement on Quality-of-Service and price. Thirdly, finding the optimal configuration requires adequate and efficient optimization techniques. The work at hand addresses these challenges through technical and economic contributions

    Cost Allocation: Methods, Principles, Applications

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    This book provides a theoretical framework for systematically evaluating the "pros" and "cons" of various methods. It also includes a series of case studies in cost allocation to give a sense of the real problems encountered in implementation. Among the examples treated are telecommunications pricing, multipurpose reservoir charges, and airport landing fees. Finally several articles address the broader fairness issues inherent in the pricing of public services. The history of the notion of the "just price" from medieval to modern times is discussed, together with observations on what principles seem to guide decisions in telecommunications rate cases in the United States. The connections between cost allocation, efficiency, and entry in the telecommunications market are also examined in two different contexts: the U.S. and France. The overall aim of the book is to provide theoretical foundations for using specific methods, to examine the distributional and fairness issues involved in cost allocation, and to give a sense of the practical problems encountered in implementation. The book will appeal to practitioners interested in what allocation methods are available, and to theorists concerned with their axiomatic foundations
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