License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.TIME.2018.22
URN: urn:nbn:de:0030-drops-97875
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9787/
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Tolonen, Lewis ; French, Tim ; Reynolds, Mark

Population Based Methods for Optimising Infinite Behaviours of Timed Automata

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LIPIcs-TIME-2018-22.pdf (0.8 MB)

Abstract

Timed automata are powerful models for the analysis of real time systems. The optimal infinite scheduling problem for double-priced timed automata is concerned with finding infinite runs of a system whose long term cost to reward ratio is minimal. Due to the state-space explosion occurring when discretising a timed automaton, exact computation of the optimal infinite ratio is infeasible. This paper describes the implementation and evaluation of ant colony optimisation for approximating the optimal schedule for a given double-priced timed automaton. The application of ant colony optimisation to the corner-point abstraction of the automaton proved generally less effective than a random method. The best found optimisation method was obtained by formulating the choice of time delays in a cycle of the automaton as a linear program and utilizing ant colony optimisation in order to determine a sequence of profitable discrete transitions comprising an infinite behaviour.

BibTeX - Entry

@InProceedings{tolonen_et_al:LIPIcs:2018:9787,
  author =	{Lewis Tolonen and Tim French and Mark Reynolds},
  title =	{{Population Based Methods for Optimising Infinite Behaviours of Timed Automata}},
  booktitle =	{25th International Symposium on Temporal Representation  and Reasoning (TIME 2018)},
  pages =	{22:1--22:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-089-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{120},
  editor =	{Natasha Alechina and Kjetil N{\o}rv{\aa}g and Wojciech Penczek},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9787},
  URN =		{urn:nbn:de:0030-drops-97875},
  doi =		{10.4230/LIPIcs.TIME.2018.22},
  annote =	{Keywords: Timed Automata, Heuristic Search, Ant Colony Optimisation}
}

Keywords: Timed Automata, Heuristic Search, Ant Colony Optimisation
Collection: 25th International Symposium on Temporal Representation and Reasoning (TIME 2018)
Issue Date: 2018
Date of publication: 08.10.2018

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