Backward Concurrent Reasoning Based on Fuzzy Petri Nets

This paper presents a backward reasoning approach based on fuzzy Petri nets (FPNs). This approach takes full advantage of the structural and behavioral properties of a FPN. It can identify middle places by a vector-computational manner rather than the conventional search way, improving inference efficiency. To reduce the complexity and scale of a FPN, man-machine interaction is introduced to it It is suggested that high efficiency and low costs which an inference method brings in practice, play a more important role than the operational efficiency of the method itself. An instance illustrates that the reasoning approach is feasible and effective.