Solving Asymmetric Decision Problems with Influence Diagrams
Artificial Intelligence
2013-02-28 v1
Abstract
While influence diagrams have many advantages as a representation framework for Bayesian decision problems, they have a serious drawback in handling asymmetric decision problems. To be represented in an influence diagram, an asymmetric decision problem must be symmetrized. A considerable amount of unnecessary computation may be involved when a symmetrized influence diagram is evaluated by conventional algorithms. In this paper we present an approach for avoiding such unnecessary computation in influence diagram evaluation.
Cite
@article{arxiv.1302.6840,
title = {Solving Asymmetric Decision Problems with Influence Diagrams},
author = {Runping Qi and Nevin Lianwen Zhang and David L. Poole},
journal= {arXiv preprint arXiv:1302.6840},
year = {2013}
}
Comments
Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)