Propagation of Belief Functions in Singly-Connected Hybrid Directed Evidential Networks
Directed evidential networks (DEVNs) can be seen, at present, as an extremely powerful graphical tool for representing and reasoning with uncertain knowledge in the framework of evidence theory.
The main purpose of this paper is twofold. Firstly, it introduces hybrid directed evidential networks which generalize the standard DEVNs. Secondly, it presents an algorithm for performing inference over singly-connected hybrid evidential networks.
- 5.Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo (1988)Google Scholar
- 7.Shenoy, P.P.: Valuation networks and conditional independence. In: Uncertainty in Artificial Intelligence, pp. 191–199 (1993)Google Scholar
- 8.Smets, Ph.: Belief function: the disjunctive rule of combination and the generalized Bayesian theorem. Int. J. Approx. Reasoning 9, 1–35 (1993)Google Scholar
- 9.Smets, Ph., Kennes, R.: The transferable belief model. Artif. Intell. 66, 191–234 (1994)Google Scholar
- 10.Xu, H., Smets, Ph.: Evidential reasoning with conditional belief functions. In: Heckerman, D., et al. (eds.) Proceedings of Uncertainty in Artificial Intelligence (UAI 1994), pp. 598–606. Morgan Kaufmann, San Mateo (1994)Google Scholar