Approximate reasoning with fuzzy Petri nets

An approach to the fuzzification of the Petri net is proposed. A token in the fuzzy Petri net (FPN) is described as a membership function of a linguistic term as opposed to a single number representing a membership value. A transition, specified as a production rule, can be fired if the distance of input tokens from the desired values is less than a given tolerance. This distance determines the difference between the output tokens produced and the output token values specified by the transition. The FPN is an excellent modeling and knowledge representation tool for all Petri net modeling applications involving imprecise token values.