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 ArticleDOI
A fair multi-attribute combinatorial double auction model for resource allocation in cloud computing
TL;DR: This work proposes a multi-attribute combinatorial double auction for the allocation of Cloud resources, which not only considers the price but other quality of service parameters also, which reflects the usefulness of the method.
Book ChapterDOI
Preference Elicitation and Query Learning
TL;DR: The authors explored the relationship between preference elicitation and query learning in combinatorial auctions and showed the similarities and differences between the two-bidder preference eliciting and the problem of query learning.
Proceedings ArticleDOI
Towards a micro-economic model for resource allocation in Grid computing systems
TL;DR: This paper uses a commodity market based approach to allocate resources, where resources are classified into different classes based on the hardware components, network connectivity, and operating system.
Journal ArticleDOI
Collective induction without cooperation? Learning and knowledge transfer in cooperative groups and competitive auctions.
TL;DR: In a series of studies involving the well-known Wason selection task, the authors demonstrate that competitive auctions induce learning effects equally impressive as those of standard group interactions, and they uncover specific and general knowledge transfers from these institutions to new reasoning problems.
Journal ArticleDOI
Pricing combinatorial auctions
TL;DR: This work finds the relationships between approaches to provide incentive compatibility and imputed, individual prices, and analyzes their advantages and disadvantages.
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.