Cargando…
Conditional Bigraphs
Bigraphs are a universal graph based model, designed for analysing reactive systems that include spatial and non-spatial (e.g. communication) relationships. Bigraphs evolve over time using a rewriting framework that finds instances of a (sub)-bigraph, and substitutes a new bigraph. In standard bigr...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314704/ http://dx.doi.org/10.1007/978-3-030-51372-6_1 |
_version_ | 1783550114277621760 |
---|---|
author | Archibald, Blair Calder, Muffy Sevegnani, Michele |
author_facet | Archibald, Blair Calder, Muffy Sevegnani, Michele |
author_sort | Archibald, Blair |
collection | PubMed |
description | Bigraphs are a universal graph based model, designed for analysing reactive systems that include spatial and non-spatial (e.g. communication) relationships. Bigraphs evolve over time using a rewriting framework that finds instances of a (sub)-bigraph, and substitutes a new bigraph. In standard bigraphs, the applicability of a rewrite rule is determined completely by a local match and does not allow any non-local reasoning, i.e. contextual conditions. We introduce conditional bigraphs that add conditions to rules and show how these fit into the matching framework for standard bigraphs. An implementation is provided, along with a set of examples. Finally, we discuss the limits of application conditions within the existing matching framework and present ways to extend the range of conditions that may be expressed. |
format | Online Article Text |
id | pubmed-7314704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73147042020-06-25 Conditional Bigraphs Archibald, Blair Calder, Muffy Sevegnani, Michele Graph Transformation Article Bigraphs are a universal graph based model, designed for analysing reactive systems that include spatial and non-spatial (e.g. communication) relationships. Bigraphs evolve over time using a rewriting framework that finds instances of a (sub)-bigraph, and substitutes a new bigraph. In standard bigraphs, the applicability of a rewrite rule is determined completely by a local match and does not allow any non-local reasoning, i.e. contextual conditions. We introduce conditional bigraphs that add conditions to rules and show how these fit into the matching framework for standard bigraphs. An implementation is provided, along with a set of examples. Finally, we discuss the limits of application conditions within the existing matching framework and present ways to extend the range of conditions that may be expressed. 2020-05-31 /pmc/articles/PMC7314704/ http://dx.doi.org/10.1007/978-3-030-51372-6_1 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Archibald, Blair Calder, Muffy Sevegnani, Michele Conditional Bigraphs |
title | Conditional Bigraphs |
title_full | Conditional Bigraphs |
title_fullStr | Conditional Bigraphs |
title_full_unstemmed | Conditional Bigraphs |
title_short | Conditional Bigraphs |
title_sort | conditional bigraphs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314704/ http://dx.doi.org/10.1007/978-3-030-51372-6_1 |
work_keys_str_mv | AT archibaldblair conditionalbigraphs AT caldermuffy conditionalbigraphs AT sevegnanimichele conditionalbigraphs |