Uncertainty in Artificial Intelligence
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Reasoning about the Value of Decision-Model Refinement: Methods and Application
Kim-Leng Poh, Eric Horvitz
Abstract:
We investigate the value of extending the completeness of a decision model along different dimensions of refinement. Specifically, we analyze the expected value of quantitative, conceptual, and structural refinement of decision models. We illustrate the key dimensions of refinement with examples. The analyses of value of model refinement can be used to focus the attention of an analyst or an automated reasoning system on extensions of a decision model associated with the greatest expected value.
Keywords:
Pages: 174-182
PS Link:
PDF Link: /papers/93/p174-poh.pdf
BibTex:
@INPROCEEDINGS{Poh93,
AUTHOR = "Kim-Leng Poh and Eric Horvitz",
TITLE = "Reasoning about the Value of Decision-Model Refinement: Methods and Application",
BOOKTITLE = "Proceedings of the Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-93)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1993",
PAGES = "174--182"
}


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