Three new sensitivity analysis methods for influence diagrams
Artificial Intelligence
2012-03-19 v1
Abstract
Performing sensitivity analysis for influence diagrams using the decision circuit framework is particularly convenient, since the partial derivatives with respect to every parameter are readily available [Bhattacharjya and Shachter, 2007; 2008]. In this paper we present three non-linear sensitivity analysis methods that utilize this partial derivative information and therefore do not require re-evaluating the decision situation multiple times. Specifically, we show how to efficiently compare strategies in decision situations, perform sensitivity to risk aversion and compute the value of perfect hedging [Seyller, 2008].
Keywords
Cite
@article{arxiv.1203.3467,
title = {Three new sensitivity analysis methods for influence diagrams},
author = {Debarun Bhattacharjya and Ross D. Shachter},
journal= {arXiv preprint arXiv:1203.3467},
year = {2012}
}
Comments
Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)