Model Checking the Ant Colony Optimisation - Distributed, Parallel and Biologically Inspired Systems Access content directly
Conference Papers Year : 2010

Model Checking the Ant Colony Optimisation

Abstract

We present a model for the travelling salesman problem (TSP) solved using the ant colony optimisation (ACO), a bio-inspired mechanism that helps speed up the search for a solution and that can be applied to many other problems. The natural complexity of the TSP combined with the self-organisation and emergent behaviours that result from the application of the ACO make model-checking this system a hard task. We discuss our approach for modelling the ACO in a well-known probabilistic model checker and describe results of verifications carried out using our model and a couple of probabilistic temporal properties. These results demonstrate not only the effectiveness of the ACO applied to the TSP, but also that our modelling approach for the ACO produces the expected behaviour. It also indicates that the same modelling could be used in other scenarios.
Fichier principal
Vignette du fichier
papermodel.pdf (398.45 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01054497 , version 1 (07-08-2014)

Licence

Attribution

Identifiers

Cite

Lucio Mauro Duarte, Luciana Foss, Flávio Rech Wagner, Tales Heimfarth. Model Checking the Ant Colony Optimisation. 7th IFIP TC 10 Working Conference on Distributed, Parallel and Biologically Inspired Systems (DIPES) / 3rd IFIP TC 10 International Conference on Biologically-Inspired Collaborative Computing (BICC) / Held as Part of World Computer Congress (WCC) , Sep 2010, Brisbane, Australia. pp.221-232, ⟨10.1007/978-3-642-15234-4_22⟩. ⟨hal-01054497⟩
140 View
192 Download

Altmetric

Share

Gmail Facebook X LinkedIn More