Extended Fuzzy Petri Nets for decision support

We present results for the formalism of extended fuzzy Petri Nets by enriching the enabling and firing rule by introducing the so-called weights and thresholds in order to filter the propagated knowledge. It is shown that knowledge propagation described using such extended fuzzy Petri nets still terminates in a unique stable state. Based on this result, the paper introduces an algorithm for knowledge propagation in medical decision support systems. We also discuss the general properties of knowledge propagation functions terminating in a unique stable state leading to the final recommendation of diagnose or treatment.