Winner Price Monotonicity for Approximated Combinatorial Auctions
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Performance Analysis about Parallel Greedy Approximation on Combinatorial Auctions
PRIMA '08 Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems
Fast Partial Reallocation in Combinatorial Auctions for Iterative Resource Allocation
Agent Computing and Multi-Agent Systems
An experimental analysis of biased parallel greedy approximation for combinatorial auctions
International Journal of Intelligent Information and Database Systems
Keyword auction protocol for dynamically adjusting the number of advertisements
Web Intelligence and Agent Systems
PRIMA'11 Proceedings of the 14th international conference on Agent Based Simulation for a Sustainable Society and Multi-agent Smart Computing
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
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Combinatorial auction, one of most popular market mechanisms, is well-known mechanism for effective resource allocation to self-interested agents. In real scenarios, since the auction mechanism has to clear the market very frequently, actually there is not enough time to compute exact optimal winners. In this paper, we show that some approximation algorithms provide sufficient quality of winners for auctions that have large number of bids but have hard time constraints. Furthermore, we compare and discuss about desirable properties of such approximation algorithms to be embedded in application systems.