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13
Mdpop: Faithful distributed implementation of efficient social choice problems
 In AAMAS’06  Autonomous Agents and Multiagent Systems
, 2006
"... In the efficient social choice problem, the goal is to assign values, subject to side constraints, to a set of variables to maximize the total utility across a population of agents, where each agent has private information about its utility function. In this paper we model the social choice problem ..."
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Cited by 41 (15 self)
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In the efficient social choice problem, the goal is to assign values, subject to side constraints, to a set of variables to maximize the total utility across a population of agents, where each agent has private information about its utility function. In this paper we model the social choice problem as a distributed constraint optimization problem (DCOP), in which each agent can communicate with other agents that share an interest in one or more variables. Whereas existing DCOP algorithms can be easily manipulated by an agent, either by misreporting private information or deviating from the algorithm, we introduce MDPOP, the first DCOP algorithm that provides a faithful distributed implementation for efficient social choice. This provides a concrete example of how the methods of mechanism design can be unified with those of distributed optimization. Faithfulness ensures that no agent can benefit by unilaterally deviating from any aspect of the protocol, neither informationrevelation, computation, nor communication, and whatever the private information of other agents. We allow for payments by agents to a central bank, which is the only central authority that we require. To achieve faithfulness, we carefully integrate the VickreyClarkeGroves (VCG) mechanism with the DPOP algorithm, such that each agent is only asked to perform computation, report
Bidding algorithms for a distributed combinatorial auction
 In Proceedings of the Autonomous Agents and MultiAgent Systems Conference
, 2007
"... Combinatorial auctions (CAs) are a great way to solve complex resource allocation and coordination problems. However, CAs require a central auctioneer who receives the bids and solves the winner determination problem, an NPhard problem. Unfortunately, a centralized auction is not a good fit for rea ..."
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Cited by 7 (1 self)
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Combinatorial auctions (CAs) are a great way to solve complex resource allocation and coordination problems. However, CAs require a central auctioneer who receives the bids and solves the winner determination problem, an NPhard problem. Unfortunately, a centralized auction is not a good fit for real world situations where the participants have proprietary interests that they wish to remain private or when it is difficult to establish a trusted auctioneer. The work presented here is motivated by the vision of distributed CAs; incentive compatible peertopeer mechanisms to solve the allocation problem, where bidders carry out the needed computation. For such a system to exist, both a protocol that distributes the computational task amongst the bidders and strategies for bidding behavior are needed. PAUSE is combinatorial auction mechanism that naturally distributes the computational load amongst the bidders, establishing the protocol or rules the participants must follow. However, it does not provide bidders with bidding strategies. This article revisits and reevaluates a set of bidding algorithms that represent different bidding strategies that bidders can use to engage in a PAUSE auction, presenting a study that analyzes them with respect to the number of goods, bids, and bidders. Results show that PAUSE, along with the aforementioned heuristic bidding algorithms, is a viable method for solving combinatorial allocation problems without a centralized auctioneer.
Quantifying the Strategyproofness of Mechanisms via
 Metrics on Payoff Distributions.” Proc. 17th National Conference on Artificial Intelligence (AAAI00
, 2009
"... Strategyproof mechanisms provide robust equilibrium with minimal assumptions about knowledge and rationality but can be unachievable in combination with other desirable properties such as budgetbalance, stability against deviations by coalitions, and computational tractability. In the search for ma ..."
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Cited by 6 (4 self)
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Strategyproof mechanisms provide robust equilibrium with minimal assumptions about knowledge and rationality but can be unachievable in combination with other desirable properties such as budgetbalance, stability against deviations by coalitions, and computational tractability. In the search for maximallystrategyproof mechanisms that simultaneously satisfy other desirable properties, we introduce a new metric to quantify the strategyproofness of a mechanism, based on comparing the payoff distribution, given truthful reports, against that of a strategyproof “reference” mechanism that solves a problem relaxation. Focusing on combinatorial exchanges, we demonstrate that the metric is informative about the eventual equilibrium, where simple regretbased metrics are not, and can be used for online selection of an effective mechanism. 1
A Kernel Method for Market Clearing
"... The problem of market clearing in an economy is that of finding prices such that supply meets demand. In this work, we propose a kernel method to compute nonlinear clearing prices for instances where linear prices do not suffice. We first present a procedure that, given a sample of values and costs ..."
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Cited by 3 (1 self)
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The problem of market clearing in an economy is that of finding prices such that supply meets demand. In this work, we propose a kernel method to compute nonlinear clearing prices for instances where linear prices do not suffice. We first present a procedure that, given a sample of values and costs for a set of bundles, implicitly computes nonlinear clearing prices by solving an appropriately formulated quadratic program. We then use this as a subroutine in an elicitation procedure that queries demand and supply incrementally over rounds, only as much as needed to reach clearing prices. An empirical evaluation demonstrates that, with a proper choice of kernel function, the method is able to find sparse nonlinear clearing prices with much less than full revelation of values and costs. When the kernel function is not suitable to clear the market, the method can be tuned to achieve approximate clearing. 1
Strong Activity Rules for Iterative Combinatorial Auctions
"... Activity rules have emerged in recent years as an important aspect of practical auction design. The role of an activity rule in an iterative auction is to suppress strategic behavior by bidders and promote simple, continual, meaningful bidding and thus, price discovery. These rules find application ..."
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Cited by 2 (0 self)
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Activity rules have emerged in recent years as an important aspect of practical auction design. The role of an activity rule in an iterative auction is to suppress strategic behavior by bidders and promote simple, continual, meaningful bidding and thus, price discovery. These rules find application in the design of iterative combinatorial auctions for real world scenarios, for example in spectrum auctions, in airline landing slot auctions, and in procurement auctions. We introduce the notion of strong activity rules, which allow simple, consistent bidding strategies while precluding all behaviors that cannot be rationalized in this way. We design such a rule for auctions with budgetconstrained bidders, i.e., bidders with valuations for resources that are greater than their ability to pay. Such bidders are of practical importance in many market environments, and hindered from bidding in a simple and consistent way by the commonly used revealedpreference activity rule, which is too strong in such an environment. We consider issues of complexity, and provide two useful forms of information feedback to guide bidders in meeting strong activity rules. As a special case, we derive a strong activity rule for non budgetconstrained bidders. The ultimate choice of activity rule must depend, in part, on beliefs about the types of bidders likely to participate in an auction event because one cannot have a rule that is simultaneously strong for both budgetconstrained bidders and quasilinear bidders.
Exact algorithms for the matrix bid auction
, 2006
"... In a combinatorial auction, multiple items are for sale simultaneously to a set of buyers. These buyers are allowed to place bids on subsets of the available items. A special kind of combinatorial auction is the socalled matrix bid auction, which was developed by Day (2004). The matrix bid auction ..."
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Cited by 1 (1 self)
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In a combinatorial auction, multiple items are for sale simultaneously to a set of buyers. These buyers are allowed to place bids on subsets of the available items. A special kind of combinatorial auction is the socalled matrix bid auction, which was developed by Day (2004). The matrix bid auction imposes restrictions on what a bidder can bid for a subsets of the items. This paper focusses on the winner determination problem, i.e. deciding which bidders should get what items. The winner determination problem of a general combinatorial auction is NPhard and inapproximable. We discuss the computational complexity of the winner determination problem for a special case of the matrix bid auction. We present two mathematical programming formulations for the general matrix bid auction winner determination problem. Based on one of these formulations, we develop two branchandprice algorithms to solve the winner determination problem. Finally, we present computational results for these algorithms and compare them with results from a branchandcut approach based on Day & Raghavan (2006).
The matrix bid auction: microeconomic properties and expressiveness
, 2006
"... A combinatorial auction is an auction where multiple items are for sale simultaneously to a set of buyers. Furthermore, buyers are allowed to place bids on subsets of the available items. This paper focusses on a combinatorial auction where a bidder can express his preferences by means of a socalle ..."
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Cited by 1 (1 self)
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A combinatorial auction is an auction where multiple items are for sale simultaneously to a set of buyers. Furthermore, buyers are allowed to place bids on subsets of the available items. This paper focusses on a combinatorial auction where a bidder can express his preferences by means of a socalled ordered matrix bid. This matrix bid auction was developed by Day (2004) and allows bids on all possible subsets, although there are restrictions on what a bidder can bid for these sets. We give an overview of how this auction works. We elaborate on the relevance of the matrix bid auction and we develop methods to verify whether a given matrix bid satisfies a number of properties related to microeconomic theory. Finally, we investigate how a collection of arbitrary bids can be represented as a matrix bid.
Combinatorial Exchanges for Coordinating Grid Services BJÖRN SCHNIZLER and
"... In this paper, two combinatorial exchange mechanisms MACE and GreedEx are introduced that are suitable for resource allocation in serviceoriented environments such as Grids. MACE provides users with a fairly complex bidding language offering flexibility in the bidding process. This flexibility come ..."
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Cited by 1 (0 self)
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In this paper, two combinatorial exchange mechanisms MACE and GreedEx are introduced that are suitable for resource allocation in serviceoriented environments such as Grids. MACE provides users with a fairly complex bidding language offering flexibility in the bidding process. This flexibility comes at the expense of computational tractability. GreedEx tremendously restricts the bidding language and thereby reduces the problem complexity considerably. As with any practical mechanism design effort, the designed artifact does not implement desirable allocations in dominant strategies. In this short paper we also introduced jCase as tool for evaluating the market outcome when agents are acting strategically on the market for Grids.
Nash Social Welfare in Multiagent Resource Allocation
"... Abstract. We study different aspects of the multiagent resource allocation problem when the objective is to find an allocation that maximizes Nash social welfare, the product of the utilities of the individual agents. The Nash solution is an important welfare criterion that combines efficiency and f ..."
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Cited by 1 (0 self)
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Abstract. We study different aspects of the multiagent resource allocation problem when the objective is to find an allocation that maximizes Nash social welfare, the product of the utilities of the individual agents. The Nash solution is an important welfare criterion that combines efficiency and fairness considerations. We show that the problem of finding an optimal outcome is NPhard for a number of different languages for representing agent preferences; we establish new results regarding convergence to Nashoptimal outcomes in a distributed negotiation framework; and we design and test algorithms similar to those applied in combinatorial auctions for computing such an outcome directly. 1
Activity Rule Paper Click here to view linked References Strong Activity Rules for Iterative Combinatorial Auctions
"... Activity rules have emerged in recent years as an important aspect of practical auction design. The role of an activity rule in an iterative auction is to suppress strategic behavior by bidders and promote simple, continual, meaningful bidding and thus, price discovery. These rules find application ..."
Abstract
 Add to MetaCart
Activity rules have emerged in recent years as an important aspect of practical auction design. The role of an activity rule in an iterative auction is to suppress strategic behavior by bidders and promote simple, continual, meaningful bidding and thus, price discovery. These rules find application in the design of iterative combinatorial auctions for real world scenarios, for example in spectrum auctions, in airline landing slot auctions, and in procurement auctions. We introduce the notion of strong activity rules, which allow simple, consistent bidding strategies while precluding all behaviors that cannot be rationalized in this way. We design such a rule for auctions with budgetconstrained bidders, i.e., bidders with valuations for resources that are greater than their ability to pay. Such bidders are of practical importance in many market environments, and hindered from bidding in a simple and consistent way by the commonly used revealedpreference activity rule, which is too strong in such an environment. We consider issues of complexity, and provide two useful forms of information feedback to guide bidders in meeting strong activity rules. As a special case, we derive a strong activity rule for non budgetconstrained bidders. The ultimate choice of activity rule must depend, in part, on beliefs about the types of bidders likely to participate in an auction event because one cannot have a rule that is simultaneously strong for both