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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Journal Article
Reallocation Problems in Agent Societies
TL;DR: In this paper, a multi-agent method based on autonomous agents endowed with a local knowledge and local interactions is proposed to solve resource reallocation problems in real-life problematics.
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Decentralized Auctioneerless Combinatorial Auctions for Multi-Unit Resource Allocation
Li-Hsing Yen,Guang Hong Sun +1 more
TL;DR: This paper proposes the first auctioneerless open-bid multi-unit combinatorial auction (MUCA) scheme that includes a BRF-based winner determination scheme that enables every agent to locally compute a critical bid value for it to win the MUCA and accordingly take its best response to other agent’s bid and win declarations.
Experiments on Combinatorial Auctions
TL;DR: This paper contains the description of experiments done so far in the combinatorial auction scenario and introduces also external objects providing services to the computees themselves, and in particular implementing a complex optimization algorithm.
Proceedings Article
Computing Stable Solutions in Threshold Network Flow Games With Bounded Treewidth
Aldo Pacchiano,Yoram Bachrach +1 more
TL;DR: Polynomial algorithms are presented for the much larger class of bounded-treewidth graphs in Threshold Network Flow Games, showing that computing the least-core in TNFGs is computationally hard, but tractable for very restricted graphs, such as layer graphs.
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.