Pulcinella: A General Tool for Propagating Uncertainty in Valuation Networks
Abstract
We present PULCinella and its use in comparing uncertainty theories. PULCinella is a general tool for Propagating Uncertainty based on the Local Computation technique of Shafer and Shenoy. It may be specialized to different uncertainty theories: at the moment, Pulcinella can propagate probabilities, belief functions, Boolean values, and possibilities. Moreover, Pulcinella allows the user to easily define his own specializations. To illustrate Pulcinella, we analyze two examples by using each of the four theories above. In the first one, we mainly focus on intrinsic differences between theories. In the second one, we take a knowledge engineer viewpoint, and check the adequacy of each theory to a given problem.
Keywords
Cite
@article{arxiv.1303.5745,
title = {Pulcinella: A General Tool for Propagating Uncertainty in Valuation Networks},
author = {Alessandro Saffiotti and Elisabeth Umkehrer},
journal= {arXiv preprint arXiv:1303.5745},
year = {2013}
}
Comments
Appears in Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence (UAI1991)