eprintid: 2056
rev_number: 13
eprint_status: archive
userid: 30
dir: disk0/00/00/20/56
datestamp: 2013-12-12 13:11:42
lastmod: 2016-07-13 10:29:47
status_changed: 2013-12-12 13:11:42
type: article
succeeds: 1536
metadata_visibility: show
creators_name: Bruni, Roberto
creators_name: Corradini, Andrea
creators_name: Gadducci, Fabio
creators_name: Lluch-Lafuente, Alberto
creators_name: Vandin, Andrea
creators_id: 
creators_id: 
creators_id: 
creators_id: alberto.lluch@imtlucca.it
creators_id: andrea.vandin@imtlucca.it
title: Modelling and analyzing adaptive self-assembling strategies with Maude
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: public
abstract: Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA.
date: 2015
date_type: published
publication: Science of Computer Programming
volume: 99
publisher: Elsevier
pagerange: 75-94
id_number: 10.1016/j.scico.2013.11.043
refereed: TRUE
issn: 0167-6423
official_url: http://www.sciencedirect.com/science/article/pii/S0167642313003389
funders: European Integrated Project 257414 ASCENS
projects: European Integrated Project 257414 ASCENS
citation:   Bruni, Roberto and Corradini, Andrea and Gadducci, Fabio and Lluch-Lafuente, Alberto and Vandin, Andrea  Modelling and analyzing adaptive self-assembling strategies with Maude.  Science of Computer Programming, 99.  pp. 75-94.  ISSN 0167-6423      (2015)  
document_url: http://eprints.imtlucca.it/2056/1/scp2013.pdf
document_url: http://eprints.imtlucca.it/2056/7/pk65.pdf
document_url: http://eprints.imtlucca.it/2056/8/scp2013.pdf
document_url: http://eprints.imtlucca.it/2056/9/scp2013.pdf