Coordinated Aggressive Bidding in Distributed. Chen, J., Bugacov, R., Szekely, P., Frank, M., Cai, M., Kim, D., & Neches, R. In In Proceedings of the AAMAS 2003 Workshop on Representations and Approaches for Time-critical Decentralized Resource/Role/Task Allocation, Melbourne , Australia, July, 2003. Paper abstract bibtex Large NP-hard combinatorial resource allocation problems are best solved via approximation techniques which produce acceptable solutions in the time available. The best of such "good-enough/soon-enough" techniques handle large problems, run in distributed environments, adapt rapidly to changes to the problem while solving, and exhibit good anytime performance.
@inproceedings{Chen:2003,
author = {Chen, Jinbo and Bugacov, Ro and Szekely, Pedro and Frank, Martin and Cai, Min and Kim, Donghan and Neches, Robert},
title = {{Coordinated Aggressive Bidding in Distributed}},
booktitle = {In Proceedings of the AAMAS 2003 Workshop on Representations and Approaches for Time-critical Decentralized Resource/Role/Task Allocation},
year = {2003},
address = {Melbourne , Australia},
month = jul,
annote = {Jinbo Chen (USC/Information Sciences Institute; 4676 Admiralty Way; Marina del Rey , CA 90292); Ro Bugacov (USC/Information Sciences Institute; 4676 Admiralty Way; Marina del Rey , CA 90292); Pedro Szekely (USC/Information Sciences Institute; 4676 Admiralty Way; Marina del Rey , CA 90292); Martin Frank (USC/Information Sciences Institute; 4676 Admiralty Way; Marina del Rey , CA 90292); Min Cai (USC/Information Sciences Institute; 4676 Admiralty Way; Marina del Rey , CA 90292); Donghan Kim (USC/Information Sciences Institute; 4676 Admiralty Way; Marina del Rey , CA 90292); Robert Neches (USC/Information Sciences Institute; 4676 Admiralty Way; Marina del Rey , CA 90292);},
language = {English},
rating = {0},
date-added = {2013-01-18T02:06:42GMT},
date-modified = {2013-05-02T16:22:57GMT},
abstract = {Large NP-hard combinatorial resource allocation problems are best solved via approximation techniques which produce acceptable solutions in the time available. The best of such "good-enough/soon-enough" techniques handle large problems, run in distributed environments, adapt rapidly to changes to the problem while solving, and exhibit good anytime performance.},
Urlpaper = {http://www.isi.edu/~szekely/contents/papers/2003/aamas2003marbles-workshop-resource-allocation.pdf},
uri = {\url{papers2://publication/uuid/B291C0F3-77EF-40A8-AFA5-C0D73EE8BDD2}}
}
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