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288
CABOB: A fast optimal algorithm for combinatorial auctions
"... Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners is-complete and inapproximable. We present CABOB, a sophisticated search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also a ..."
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Cited by 137 (26 self)
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Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners is-complete and inapproximable. We present CABOB, a sophisticated search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also across components), elaborate and dynamically chosen bid ordering heuristics, and a host of structural observations. Experiments against CPLEX 7.0 show that CABOB is usually faster, never drastically slower, and in many cases drastically faster. We also uncover interesting aspects of the problem itself. First, the problems with short bids that were hard for the first-generation of specialized algorithms are easy. Second, almost all of the CATS distributions are easy, and become easier with more bids. Third, we test a number of random restart strategies, and show that they do not help on this problem because the run-time distribution does not have a heavy tail (at least not for CABOB). 1
eMediator: A Next Generation Electronic Commerce Server
- Computational Intelligence
, 2002
"... This paper presents eMediator, an electronic commerce server prototype that demonstrates ways in which algorithmic support and game-theoretic incentive engineering can jointly improve the efficiency of ecommerce. eAuctionHouse, the configurable auction server, includes a variety of generalized combi ..."
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Cited by 123 (32 self)
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This paper presents eMediator, an electronic commerce server prototype that demonstrates ways in which algorithmic support and game-theoretic incentive engineering can jointly improve the efficiency of ecommerce. eAuctionHouse, the configurable auction server, includes a variety of generalized combinatorial auctions and exchanges, pricing schemes, bidding languages, mobile agents, and user support for choosing an auction type. We introduce two new logical bidding languages for combinatorial markets: the XOR bidding language and the OR-of-XORs bidding language. Unlike the traditional OR bidding language, these are fully expressive. They therefore enable the use of the Clarke-Groves pricing mechanism for motivating the bidders to bid truthfully. eAuctionHouse also supports supply/demand curve bidding. eCommitter, the leveled commitment contract optimizer, determines the optimal contract price and decommitting penalties for a variety of leveled commitment contracting mechanisms, taking into account that rational agents will decommit strategically in Nash equilibrium. It also determines the optimal decommitting strategies for any given leveled commitment contract. eExchangeHouse, the safe exchange planner, enables unenforced anonymous exchanges by dividing the exchange into chunks and sequencing those chunks to be delivered safely in alternation between the buyer and the seller.
iBundle: An Efficient Ascending Price Bundle Auction
- In ACM Conference on Electronic Commerce
, 1999
"... Standard auction mechanisms often break down in important e-commerce applications, where agents demand bundles of complementary resources, i.e. "I only want B if I also get A". This paper describes Bundle, an ascending-price auction that is guaranteed to compute optimal bundle allocations ..."
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Cited by 118 (12 self)
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Standard auction mechanisms often break down in important e-commerce applications, where agents demand bundles of complementary resources, i.e. "I only want B if I also get A". This paper describes Bundle, an ascending-price auction that is guaranteed to compute optimal bundle allocations with agents that follow a best-response bidding strategy. The auction prices bundles directly and allows agents to place additive or exclusive-or bids over collections of bundles. Empirical results confirm that Bundle generates efficient allocations for hard resource allocation problems. Furthermore, we show that Bundle generates solutions without complete revelation (or computation) of agent preferences. Keywords Iterative auction, agent-mediated electronic commerce, resource allocation, bundling problem, price discrimination.
B.J.: A combinatorial auction for collaborative planning. In:
- Proceedings International Conference on Multi-Agent Systems (ICMAS-00).
, 2000
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On agent-mediated electronic commerce
- IEEE Transactions on Knowledge and Data Engineering
, 2003
"... Abstract—This paper surveys and analyzes the state of the art of agent-mediated electronic commerce (e-commerce), concentrating particularly on the business-to-consumer (B2C) and business-to-business (B2B) aspects. From the consumer buying behavior perspective, agents are being used in the following ..."
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Cited by 111 (15 self)
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Abstract—This paper surveys and analyzes the state of the art of agent-mediated electronic commerce (e-commerce), concentrating particularly on the business-to-consumer (B2C) and business-to-business (B2B) aspects. From the consumer buying behavior perspective, agents are being used in the following activities: need identification, product brokering, buyer coalition formation, merchant brokering, and negotiation. The roles of agents in B2B e-commerce are discussed through the business-to-business transaction model that identifies agents as being employed in partnership formation, brokering, and negotiation. Having identified the roles for agents in B2C and B2B e-commerce, some of the key underpinning technologies of this vision are highlighted. Finally, we conclude by discussing the future directions and potential impediments to the wide-scale adoption of agent-mediated e-commerce. Index Terms—Agent-mediated electronic commerce, intelligent agents. 1
Preference Elicitation in Combinatorial Auctions (Extended Abstract)
- IN PROCEEDINGS OF THE ACM CONFERENCE ON ELECTRONIC COMMERCE (ACM-EC
, 2001
"... Combinatorial auctions (CAs) where bidders can bid on bundles of items can be very desirable market mechanisms when the items sold exhibit complementarity and/or substitutability, so the bidder's valuations for bundles are not additive. However, in a basic CA, the bidders may need to bid on e ..."
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Cited by 108 (27 self)
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Combinatorial auctions (CAs) where bidders can bid on bundles of items can be very desirable market mechanisms when the items sold exhibit complementarity and/or substitutability, so the bidder's valuations for bundles are not additive. However, in a basic CA, the bidders may need to bid on exponentially many bundles, leading to di#culties in determining those valuations, undesirable information revelation, and unnecessary communication. In this paper we present a design of an auctioneer agent that uses topological structure inherent in the problem to reduce the amount of information that it needs from the bidders. An analysis tool is presented as well as data structures for storing and optimally assimilating the information received from the bidders. Using this information, the agent then narrows down the set of desirable (welfare-maximizing or Pareto-e#cient) allocations, and decides which questions to ask next. Several algorithms are presented that ask the bidders for value, order, and rank information. A method is presented for making the elicitor incentive compatible.
Sequential auctions for the allocation of resources with complementarities
, 1999
"... Market-based mechanisms such as auctions are being studied as an appropriate means for resource allocation in distributed and inultiagcnl decision problems. When agents value resources in combination rather than in isolation, one generally relies on combinatorial auctions where agents bid tor resour ..."
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Cited by 106 (2 self)
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Market-based mechanisms such as auctions are being studied as an appropriate means for resource allocation in distributed and inultiagcnl decision problems. When agents value resources in combination rather than in isolation, one generally relies on combinatorial auctions where agents bid tor resource bundles. or simultaneous auctions for all resources. We develop a different model, where agents bid for required resources sequentially. This model has the advantage that it can be applied in settings where combinatorial and simultaneous models are infeasible (e.g.. when resources are made available at different points in time by different parties), as well as certain benefits in settings where combinatorial models are applicable. We develop a dynamic programming model tor agents to compute bidding policies based on estimated distributions over prices. We also describe how these distributions are updated to provide a learning model for bidding behavior.
Solving Combinatorial Auctions using Stochastic Local Search
, 2000
"... Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determination for CAs is NP-hard and recent algorithms have difficulty with problems involving goods and bids beyond the hundre ..."
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Cited by 106 (2 self)
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Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determination for CAs is NP-hard and recent algorithms have difficulty with problems involving goods and bids beyond the hundreds. We apply a new stochastic local search algorithm, Casanova, to this problem, and demonstrate that it finds high quality (even optimal) solutions much faster than recently proposed methods (up to several orders of magnitude), particularly for large problems. We also propose a logical language for naturally expressing combinatorial bids in which a single logical bid corresponds to a large (often exponential) number of explicit bids. We show that Casanova performs much better than systematic methods on such problems.
Issues in multiagent resource allocation
- INFORMATICA
, 2006
"... The allocation of resources within a system of autonomous agents, that not only have preferences over alternative allocations of resources but also actively participate in computing an allocation, is an exciting area of research at the interface of Computer Science and Economics. This paper is a sur ..."
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Cited by 104 (17 self)
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The allocation of resources within a system of autonomous agents, that not only have preferences over alternative allocations of resources but also actively participate in computing an allocation, is an exciting area of research at the interface of Computer Science and Economics. This paper is a survey of some of the most salient issues in Multiagent Resource Allocation. In particular, we review various languages to represent the preferences of agents over alternative allocations of resources as well as different measures of social welfare to assess the overall quality of an allocation. We also discuss pertinent issues regarding allocation procedures and present important complexity results. Our presentation of theoretical issues is complemented by a discussion of software packages for the simulation of agent-based market places. We also introduce four major application areas for Multiagent Resource Allocation, namely industrial procurement, sharing of satellite resources, manufacturing control, and grid computing.
Bidding languages for combinatorial auctions
- In Proc. 17th Intl. Joint Conference on Artif. Intell
, 2001
"... Combinatorial auctions provide a valuable mechanism for the allocation of goods in settings where buyer valuations exhibit complex structure with respect to substitutabilityand complementarity. Most algorithms are designed to work with explicit bids for concrete bundles of goods. However, logical bi ..."
Abstract
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Cited by 98 (1 self)
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Combinatorial auctions provide a valuable mechanism for the allocation of goods in settings where buyer valuations exhibit complex structure with respect to substitutabilityand complementarity. Most algorithms are designed to work with explicit bids for concrete bundles of goods. However, logical bidding languages allow the expression of complex utility functions in a natural and concise way. We introduce a new, generalized language where bids are given by propositional formulae whose subformulae can be annotated with prices. This language allows bidder utilities to be formulated more naturally and concisely than existing languages. Furthermore, we outline a general algorithmic technique for winner determination for auctions that use this bidding language. 1
