Encoding Reversing Petri Nets in Answer Set Programming

Reversing Petri nets (RPNs) have been proposed as a reversible approach to Petri nets, which allows the transitions of a net to be reversed. This work presents an approach towards an implementation of RPNs to support their simulation and analysis. Specifically, we define how to model RPNs in Answer Set Programming (ASP), a declarative programming framework with competitive solvers. We highlight how the methodology can be used to reason about the behavior of RPN models.