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Evolutionary Petri Nets.

Project description

Evolutionary Petri Net

*Evolutionary Petri Nets* (EPN) is a convenient tool for the automatic
inference, optimization, and reverse engineering of Petri Nets (PNs). The
library exploits the evolutionary computation methodology described in [1].

WARNING: this is a preliminary alpha release.

EPN can be used as follows:

#!/usr/bin/env python

from epn.hpn import *
from epn.evolpn import *
from epn.basic import *


E = EvolutionaryPetriNet()
for p in range(POPULATION):
p = ResizablePetriNet("H"+str(p))
E.setFitnessFunction( ... )

EPN can produce output figures of the PNs by using the dot/graphviz library.
For this reason, EPN relies on the external library pydot. The current state
of the whole EPN can be outputted with the following command:



EPNs does not directly handle PNs, but it exploits an extended class named
*Resizable Petri Net* (RPN). A population of RPNs undergoes an evolutionary
process, in which the best individuals are iteratively modified and improved
by means of crossover and mutation operators. The evolutive pressure is driven
by a user-defined fitness function.

The programmer is given the freedom of choosing

* the population size;

* one of the selection mechanism (roulette wheel, ranking, tournament);

* the maximum number of iterations;

* the pre- and post-order of transitions (see [1] for further information).

Thanks also to

EPNs have been developed by a joint effort of M.S. Nobile and G. Mauri
(University of Milan-Bicocca, Italy), D. Besozzi (University of Milan, Italy)
and P. Cazzaniga (University of Bergamo, Italy).

Further information:

[1] Nobile, Besozzi, Cazzaniga and Mauri, "The Foundations of Evolutionary
Petri Nets", Proceedings of the 4th International Workshop on Biological
Processes & Petri Nets (BioPPN 2013), a satellite event of PETRI NETS 2013
(G. Balbo and M. Heiner, eds.), CEUR Workshop Proceedings Vol. 988, 60-74, 2013


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