Model Checking the Ant Colony Optimisation

  • Lucio Mauro Duarte
  • Luciana Foss
  • Flávio Rech Wagner
  • Tales Heimfarth
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 329)

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.

Keywords

ant colony optimisation self-organisation emergent behaviour probabilistic model checking 

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Copyright information

© IFIP 2010

Authors and Affiliations

  • Lucio Mauro Duarte
    • 1
  • Luciana Foss
    • 2
  • Flávio Rech Wagner
    • 1
  • Tales Heimfarth
    • 3
  1. 1.Institute of InformaticsFederal University of Rio Grande do SulBrazil
  2. 2.Institute of Physics and Mathematics, DINFOFederal University of PelotasBrazil
  3. 3.Dep. of Computer ScienceFederal University of LavrasBrazil

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