Uncertainty in Artificial Intelligence
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Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation
Craig Boutilier, Rajarshi Das, Jeffrey Kephart, Gerald Tesauro, William Walsh
Abstract:
Decentralized resource allocation is a key problem for large-scale autonomic (or self-managing) computing systems. Motivated by a data center scenario, we explore efficient techniques for resolving resource conflicts via cooperative negotiation. Rather than computing in advance the functional dependence of each element's utility upon the amount of resource it receives, which could be prohibitively expensive, each element's utility is elicited incrementally. Such incremental utility elicitation strategies require the evaluation of only a small set of sampled utility function points, yet they find near-optimal allocations with respect to a minimax regret criterion. We describe preliminary computational experiments that illustrate the benefit of our approach.
Keywords:
Pages: 89-97
PS Link:
PDF Link: /papers/03/p89-boutilier.pdf
BibTex:
@INPROCEEDINGS{Boutilier03,
AUTHOR = "Craig Boutilier and Rajarshi Das and Jeffrey Kephart and Gerald Tesauro and William Walsh",
TITLE = "Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation",
BOOKTITLE = "Proceedings of the Nineteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2003",
PAGES = "89--97"
}


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