On the Use of Possibilistic Bases for Local Computations in Product-Based Possibilistic Networks

摘要

Product-based possibilistic networks allow an efficient representation of possibility distributions. However, when the graph is multiply connected, the propagation may be unfeasible because of the high space complexity problem. In this paper, we propose a new inference approach on product-based possibilistic networks based on compact representations of possibility distributions, which are possibilistic knowledge bases.