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Sensitivity analysis in decision circuits

Conference Paper Accepted Paper Artificial Intelligence · Machine Learning · Uncertainty in Artificial Intelligence

Abstract

Decision circuits have been developed to perform efficient evaluation of influence diagrams [Bhattacharjya and Shachter, 2007], building on the advances in arithmetic circuits for belief network inference [Darwiche, 2003]. In the process of model building and analysis, we perform sensitivity analysis to understand how the optimal solution changes in response to changes in the model. When sequential decision problems under uncertainty are represented as decision circuits, we can exploit the efficient solution process embodied in the decision circuit and the wealth of derivative information available to compute the value of information for the uncertainties in the problem and the effects of changes to model parameters on the value and the optimal strategy.

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Context

Venue
Conference on Uncertainty in Artificial Intelligence
Archive span
1985-2025
Indexed papers
3717
Paper id
928313856460746485