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Bibliographic Details
Main Author: Capra, Lorenzo
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2502.09217
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author Capra, Lorenzo
author_facet Capra, Lorenzo
contents Petri Nets (PN) are widely used for modeling concurrent and distributed systems, but face challenges in modeling adaptive systems. To address this, we have formalized "rewritable" PT nets (RwPT) using Maude, a declarative language with sound rewriting logic semantics. Recently, we introduced a modular approach that utilizes algebraic operators to construct large RwPT models. This technique employs composite node labeling to outline symmetries in hierarchical organization, preserved through net rewrites. Once stochastic parameters are added to the formalism, we present an automated process to derive a lumped CTMC from the quotient graph generated by an RwPT.
format Preprint
id arxiv_https___arxiv_org_abs_2502_09217
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Modular Stochastic Rewritable Petri Nets
Capra, Lorenzo
Performance
Symbolic Computation
Petri Nets (PN) are widely used for modeling concurrent and distributed systems, but face challenges in modeling adaptive systems. To address this, we have formalized "rewritable" PT nets (RwPT) using Maude, a declarative language with sound rewriting logic semantics. Recently, we introduced a modular approach that utilizes algebraic operators to construct large RwPT models. This technique employs composite node labeling to outline symmetries in hierarchical organization, preserved through net rewrites. Once stochastic parameters are added to the formalism, we present an automated process to derive a lumped CTMC from the quotient graph generated by an RwPT.
title Modular Stochastic Rewritable Petri Nets
topic Performance
Symbolic Computation
url https://arxiv.org/abs/2502.09217