Algorithm for optimal winner determination in combinatorial auctions
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TLDR
The algorithm allows combinatorial auctions to scale up to significantly larger numbers of items and bids than prior approaches to optimal winner determination by capitalizing on the fact that the space of bids is sparsely populated in practice.About:
This article is published in Artificial Intelligence.The article was published on 2002-02-01 and is currently open access. It has received 1045 citations till now. The article focuses on the topics: Combinatorial auction & Common value auction.read more
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Logical Preference Representation and Combinatorial Vote
TL;DR: This work introduces the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of non-independent variables to assign.
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Economic reasoning and artificial intelligence
TL;DR: This work asks how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people.
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BOB: improved winner determination in combinatorial auctions and generalizations
Tuomas Sandholm,Subhash Suri +1 more
TL;DR: A more sophisticated search algorithm for optimal (and anytime) winner determination is presented, including structural improvements that reduce search tree size, faster data structures, and optimizations at search nodes based on driving toward, identifying and solving tractable special cases.
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Negotiating socially optimal allocations of resources
TL;DR: This paper studies an abstract negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources and shows how certain classes of deals are both sufficient and necessary to guarantee that a socially optimal allocation of resources will be reached eventually.
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Approaches to winner determination in combinatorial auctions
TL;DR: eMediator, the first Internet auction to support combinatorial auctions, bidding via graphically drawn price–quantity graphs, and by mobile agents, is discussed, and a new search algorithm for optimal anytime winner determination is overview, capitalizing on the fact that the space of bids is necessarily sparsely populated in practice.
References
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Book
Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Book ChapterDOI
Reducibility Among Combinatorial Problems
TL;DR: The work of Dantzig, Fulkerson, Hoffman, Edmonds, Lawler and other pioneers on network flows, matching and matroids acquainted me with the elegant and efficient algorithms that were sometimes possible.
Book
Integer programming
TL;DR: The principles of integer programming are directed toward finding solutions to problems from the fields of economic planning, engineering design, and combinatorial optimization as mentioned in this paper, which is a standard of graduate-level courses since 1972.
Journal ArticleDOI
Incentives in Teams
TL;DR: This paper analyzes the problem of inducing the members of an organization to behave as if they formed a team and exhibits a particular set of compensation rules, an optimal incentive structure, that leads to team behavior.