Application of Binary Petri Nets to Knowledge Representation and Inference

In this paper, we present a binary Petri net model designed for knowledge representation and inference in rule-based systems. We assume that knowledge and inference in such systems is expressed in the formalism of classic logic. The usefulness of binary Petri nets is analyzed as an example of a simple rule-based train traffic control system. The exemplary model was additionally subjected to experimental verification and assessed using artificially generated test data for this model.