Reasoning about the Value of Decision-Model Refinement: Methods and Application
Artificial Intelligence
2013-03-08 v1
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.
Cite
@article{arxiv.1303.1475,
title = {Reasoning about the Value of Decision-Model Refinement: Methods and Application},
author = {Kim-Leng Poh and Eric J. Horvitz},
journal= {arXiv preprint arXiv:1303.1475},
year = {2013}
}
Comments
Appears in Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (UAI1993)