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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Comparing Multiagent Systems Research in Combinatorial Auctions and Voting.
TL;DR: A convenient side-by-side comparison is given that will clarify the relation between the domains combinatorial auction and voting, and serve as a guide to future research.
Proceedings Article
Weighted super solutions for constraint programs
Alan Holland,Barry O'Sullivan +1 more
TL;DR: This paper presents the weighted super solution framework that involves two important extensions: the set of variables that may lose their values is determined using a probabilistic approach enabling us to find repair solutions for assignments that are most likely to fail and a mechanism for reasoning about the cost of repair.
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Design issues for combinatorial auctions
TL;DR: This paper discusses several complex issues related to the formulation of the winner determination problem, the expression of combined bids, the design of progressive combinatorial auctions that require less information revelation, and the need for decision support tools to help participants make profitable bidding decisions.
Proceedings Article
On the complexity of compact coalitional games
TL;DR: A significantly complete account of the complexity underlying the computation of relevant solution concepts in compact coalitional games is provided, and new insights are provided on this setting by stating a number of complexity results about some relevant generalizations and specializations.
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Online Set Packing
Yuval Emek,Magnús M. Halldórsson,Yishay Mansour,Boaz Patt-Shamir,Jaikumar Radhakrishnan,Dror Rawitz +5 more
TL;DR: This work presents a randomized competitive online algorithm for the weighted case with general capacity (namely, where sets may have different values, and elements arrive with different multiplicities), and proves a matching lower bound on the competitive ratio for any randomized online algorithm.
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.
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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.
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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.